250+ Fine-tuning & RL Notebooks for text, vision, audio, embedding, TTS models.
This report presents the forensic synthetic code analysis of unslothai/notebooks, a Jupyter Notebook project with 5,512 GitHub stars. SynthScan v2.0 examined 323,714 lines of code across 612 source files, recording 6840 pattern matches distributed across 21 syntactic categories. The overall adjusted score of 58.6 places this repository in the Strong AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 6840 distinct pattern matches across 21 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | update_all_notebooks.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_Embedding_(0_6B).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Granite4.0_350M.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/GLM_Flash_A100(80GB).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma4_(E2B)-Text.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_6_MoE.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/gpt_oss_(20B)_GRPO_BF16.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/FunctionGemma_(270M).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma4_(12B)_Text.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma3_(270M)_Phone_Deployment.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Magistral_(24B)-Reasoning-Conversational.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Liquid_LFM2_(1.2B)-Conversational.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Llama3.2_(1B_and_3B)-Conversational.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Pixtral_(12B)-Vision.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Granite4.0.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Deepseek_OCR_2_(3B).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/DiffusionGemma_(26B-A4B)-Sudoku.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Sesame_CSM_(1B)-TTS.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_VL_(8B)-Vision-GRPO.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma4_(E4B)-Text.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Llasa_TTS_(1B).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Mistral_Nemo_(12B)-Alpaca.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_5_(2B)_Vision.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma2_(9B)-Alpaca.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/gpt-oss-(20B)-Fine-tuning.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma4_(E4B)-Audio.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Phi_3_Medium-Conversational.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_(32B)_A100-Reasoning-Conversational.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Llama3.1_(8B)-Alpaca.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma4_(12B)_Vision.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/gpt-oss-(120B)_A100-Fine-tuning.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma4_(26B_A4B)-Text.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_(14B).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Liquid_LFM2-Conversational.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Spark_TTS_(0_5B).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma3_(270M).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_5_(4B)_Vision_GRPO.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/ModernBert.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma3_(4B)-Vision.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | …CodeForces-cot-Finetune_for_Reasoning_on_CodeForces.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Llama3.2_(11B)-Vision.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma4_(12B)_Audio.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/gpt_oss_(20B)_500K_Context_Fine_tuning.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Nemotron-Nano-3-30B-A3B_A100.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_(4B)-Instruct.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Llama3.2_(1B)-RAFT.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/LFM2.5_(1.2B)-Translation.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen2.5_(7B)-Alpaca.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_(4B)-Thinking.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_5_(4B)_Vision.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/GPT_OSS_MXFP4_(20B)-Inference.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/FunctionGemma_(270M)-Mobile-Actions.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Qwen3_MoE.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Llama3_(8B)-ORPO.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Llama3_(8B)-Conversational.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Zephyr_(7B)-DPO.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Ministral_3_VL_(3B)_Vision.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/Gemma3N_(4B)-Audio.py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| HIGH | molab/EmbeddingGemma_(300M).py | 0 | introducing **unsloth studio** - a new open source, no-code web ui to train and run llms. [blog](https://unsloth.ai/docs | STRING |
| 2424 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | pyproject.toml | 21 | # names it had to rename for the single-definition rule, which | COMMENT |
| LOW | update_all_notebooks.py | 1 | # Unsloth Notebooks - Notebooks for Unsloth | COMMENT |
| LOW | update_all_notebooks.py | 541 | COMMENT | |
| LOW | update_all_notebooks.py | 3061 | # popularity (downloads + likes*1000) of the models each notebook actually | COMMENT |
| LOW | update_all_notebooks.py | 3621 | return cache, refs_by_nb, assigned_by_nb | COMMENT |
| LOW | update_all_notebooks.py | 4861 | model_type = info['type'] if info and info['type'] else "" | COMMENT |
| LOW | update_all_notebooks.py | 5101 | # cross-listed GRPO / RL rows to the top so readers scanning the | COMMENT |
| LOW | molab/Qwen3_Embedding_(0_6B).py | 1 | # /// script | COMMENT |
| LOW | molab/Granite4.0_350M.py | 1 | # /// script | COMMENT |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 1 | # /// script | COMMENT |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 21 | # "uvicorn", | COMMENT |
| LOW | molab/GLM_Flash_A100(80GB).py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(E2B)-Text.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(E2B)-Text.py | 21 | # "unsloth_zoo @ git+https://github.com/unslothai/unsloth-zoo", | COMMENT |
| LOW | molab/Qwen3_6_MoE.py | 1 | # /// script | COMMENT |
| LOW | molab/Qwen3_6_MoE.py | 21 | # "xformers>=0.0.33", | COMMENT |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 1 | # /// script | COMMENT |
| LOW | molab/NeMo-Gym-Multi-Environment.py | 1 | # /// script | COMMENT |
| LOW | molab/NeMo-Gym-Multi-Environment.py | 121 | @app.cell | COMMENT |
| LOW | molab/FunctionGemma_(270M).py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(12B)_Text.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(12B)_Text.py | 21 | # "unsloth_zoo @ git+https://github.com/unslothai/unsloth-zoo", | COMMENT |
| LOW | molab/Gemma3_(270M)_Phone_Deployment.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma3_(270M)_Phone_Deployment.py | 21 | # "unsloth @ git+https://github.com/unslothai/unsloth", | COMMENT |
| LOW | molab/Gemma3_(270M)_Phone_Deployment.py | 361 | """) | COMMENT |
| LOW | molab/Gemma3_(270M)_Phone_Deployment.py | 421 | ### Test Inference on Exported Model | COMMENT |
| LOW | molab/Magistral_(24B)-Reasoning-Conversational.py | 1 | # /// script | COMMENT |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 1 | # /// script | COMMENT |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 21 | # "uvicorn", | COMMENT |
| LOW | molab/Liquid_LFM2_(1.2B)-Conversational.py | 1 | # /// script | COMMENT |
| LOW | molab/Llama3.2_(1B_and_3B)-Conversational.py | 1 | # /// script | COMMENT |
| LOW | molab/Pixtral_(12B)-Vision.py | 1 | # /// script | COMMENT |
| LOW | molab/Granite4.0.py | 1 | # /// script | COMMENT |
| LOW | molab/Deepseek_OCR_2_(3B).py | 1 | # /// script | COMMENT |
| LOW | molab/Deepseek_OCR_2_(3B).py | 21 | # "unsloth @ git+https://github.com/unslothai/unsloth", | COMMENT |
| LOW | molab/DiffusionGemma_(26B-A4B)-Sudoku.py | 1 | # /// script | COMMENT |
| LOW | molab/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 1 | # /// script | COMMENT |
| LOW | molab/Sesame_CSM_(1B)-TTS.py | 1 | # /// script | COMMENT |
| LOW | molab/Synthetic_Data_Hackathon.py | 1 | # /// script | COMMENT |
| LOW | molab/Qwen3_VL_(8B)-Vision-GRPO.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(E4B)-Text.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(E4B)-Text.py | 21 | # "unsloth_zoo @ git+https://github.com/unslothai/unsloth-zoo", | COMMENT |
| LOW | molab/Llasa_TTS_(1B).py | 1 | # /// script | COMMENT |
| LOW | molab/Llasa_TTS_(1B).py | 21 | # "trl==0.15.2", | COMMENT |
| LOW | molab/Mistral_Nemo_(12B)-Alpaca.py | 1 | # /// script | COMMENT |
| LOW | molab/Qwen3_5_(2B)_Vision.py | 1 | # /// script | COMMENT |
| LOW | molab/Qwen3_5_(2B)_Vision.py | 21 | # "xformers>=0.0.33", | COMMENT |
| LOW | molab/Gemma2_(9B)-Alpaca.py | 1 | # /// script | COMMENT |
| LOW | molab/gpt-oss-(20B)-Fine-tuning.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(E4B)-Audio.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(E4B)-Audio.py | 21 | # "unsloth_zoo @ git+https://github.com/unslothai/unsloth-zoo", | COMMENT |
| LOW | molab/Phi_3_Medium-Conversational.py | 1 | # /// script | COMMENT |
| LOW | molab/Qwen3_(32B)_A100-Reasoning-Conversational.py | 1 | # /// script | COMMENT |
| LOW | molab/Llama3.1_(8B)-Alpaca.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(12B)_Vision.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(12B)_Vision.py | 21 | # "unsloth_zoo @ git+https://github.com/unslothai/unsloth-zoo", | COMMENT |
| LOW | molab/Openenv_wordle_grpo.py | 1 | # /// script | COMMENT |
| LOW | molab/Openenv_wordle_grpo.py | 21 | # "uvicorn", | COMMENT |
| LOW | molab/gpt-oss-(120B)_A100-Fine-tuning.py | 1 | # /// script | COMMENT |
| LOW | molab/Gemma4_(26B_A4B)-Text.py | 1 | # /// script | COMMENT |
| 2155 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH⚡ | update_all_notebooks.py | 557 | ROCM_TAG="$({ command -v amd-smi >/dev/null 2>&1 && amd-smi version 2>/dev/null | awk -F'ROCm version: ' 'NF>1{split($2, | CODE |
| HIGH⚡ | update_all_notebooks.py | 557 | ROCM_TAG="$({ command -v amd-smi >/dev/null 2>&1 && amd-smi version 2>/dev/null | awk -F'ROCm version: ' 'NF>1{split($2, | CODE |
| HIGH | update_all_notebooks.py | 383 | !rm -rf OuteTTS && git clone https://github.com/edwko/OuteTTS | CODE |
| HIGH | update_all_notebooks.py | 393 | !rm -rf OuteTTS && git clone https://github.com/edwko/OuteTTS | CODE |
| HIGH | update_all_notebooks.py | 648 | !git clone https://github.com/sgl-project/sglang.git && cd sglang && pip install -e "python[all]" | CODE |
| HIGH | update_all_notebooks.py | 701 | !pip install transformers==4.55.4 && pip install --no-deps trl==0.22.2""".replace( | CODE |
| HIGH⚡ | molab/NeMo-Gym-Multi-Environment.py | 194 | ["bash", "-c", "source .venv/bin/activate && uv sync"], | STRING |
| HIGH⚡ | molab/NeMo-Gym-Multi-Environment.py | 199 | ["bash", "-c", "source .venv/bin/activate && uv pip install reasoning-gym"], | STRING |
| HIGH⚡ | molab/NeMo-Gym-Multi-Environment.py | 205 | ["bash", "-c", "source .venv/bin/activate && uv pip install matplotlib"], | STRING |
| HIGH⚡ | molab/NeMo-Gym-Multi-Environment.py | 220 | "source .venv/bin/activate && python " | STRING |
| HIGH | molab/NeMo-Gym-Multi-Environment.py | 272 | "source .venv/bin/activate && ng_run " | STRING |
| HIGH⚡ | molab/NeMo-Gym-Sudoku.py | 188 | ["bash", "-c", "source .venv/bin/activate && uv sync"], | STRING |
| HIGH⚡ | molab/NeMo-Gym-Sudoku.py | 193 | ["bash", "-c", "source .venv/bin/activate && uv pip install reasoning-gym"], | STRING |
| HIGH⚡ | molab/NeMo-Gym-Sudoku.py | 199 | ["bash", "-c", "source .venv/bin/activate && uv pip install matplotlib"], | STRING |
| HIGH⚡ | molab/NeMo-Gym-Sudoku.py | 214 | "source .venv/bin/activate && python " | STRING |
| HIGH | molab/NeMo-Gym-Sudoku.py | 234 | "source .venv/bin/activate && ng_run " | STRING |
| HIGH | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 26 | get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comman | CODE |
| HIGH | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 26 | get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comman | CODE |
| HIGH | python_scripts/AMD-Pixtral_(12B)-Vision.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma3_(4B).py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Liquid_LFM2_(1.2B)-Conversational.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-CodeGemma_(7B)-Conversational.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma3N_(2B)-Inference.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma4_(26B_A4B)-Vision.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 139 | ["bash", "-c", "source .venv/bin/activate && uv sync"], | CODE |
| HIGH⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 143 | ["bash", "-c", "source .venv/bin/activate && uv pip install reasoning-gym"], | CODE |
| HIGH⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 148 | ["bash", "-c", "source .venv/bin/activate && uv pip install matplotlib"], | CODE |
| HIGH⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 160 | "source .venv/bin/activate && python " | CODE |
| HIGH | python_scripts/NeMo-Gym-Multi-Environment.py | 210 | "source .venv/bin/activate && ng_run " | CODE |
| HIGH | python_scripts/AMD-Llama3.1_(8B)-Inference.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Spark_TTS_(0_5B).py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma3_(4B)-Vision.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma4_(12B)_Text.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 123 | ["bash", "-c", "source .venv/bin/activate && uv sync"], | CODE |
| HIGH⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 127 | ["bash", "-c", "source .venv/bin/activate && uv pip install reasoning-gym"], | CODE |
| HIGH⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 132 | ["bash", "-c", "source .venv/bin/activate && uv pip install matplotlib"], | CODE |
| HIGH⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 144 | "source .venv/bin/activate && python " | CODE |
| HIGH | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 21 | get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comman | CODE |
| HIGH | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 21 | get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comman | CODE |
| HIGH | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 194 | "source .venv/bin/activate && ng_run " | CODE |
| HIGH | python_scripts/AMD-GLM_Flash_A100(80GB).py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma4_(12B)_Audio.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | …thon_scripts/AMD-Qwen2.5_Coder_(14B)-Conversational.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma4_(E2B)-Text.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | …thon_scripts/AMD-Llama3.3_(70B)_A100-Conversational.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-TinyLlama_(1.1B)-Alpaca.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-FunctionGemma_(270M).py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma3_(270M)_Phone_Deployment.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | …hon_scripts/AMD-FunctionGemma_(270M)-Mobile-Actions.py | 28 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 18 | get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comman | CODE |
| HIGH | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 18 | get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comman | CODE |
| HIGH | python_scripts/AMD-Deepseek_OCR_(3B)-Evaluation.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Llama3.1_(8B)-Alpaca.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Nemotron-3-Nano-30B-A3B_A100.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Qwen_3_5_27B_A100(80GB).py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Llama3_(8B)-ORPO.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Qwen3_(4B)_Instruct-QAT.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| HIGH | python_scripts/AMD-Gemma3N_(4B)-Vision.py | 37 | # get_ipython().run_cell_magic('bash', '', 'python -m pip install -qU uv --root-user-action=ignore\n\nROCM_TAG="$({ comm | COMMENT |
| 144 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | update_all_notebooks.py | 542 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | update_all_notebooks.py | 552 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | update_all_notebooks.py | 3056 | # ============================================================================ | COMMENT |
| MEDIUM | update_all_notebooks.py | 3058 | # ============================================================================ | COMMENT |
| MEDIUM | tests/test_molab_no_colab_markers.py | 47 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_no_colab_markers.py | 49 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_no_colab_markers.py | 62 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_no_colab_markers.py | 64 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_no_colab_markers.py | 72 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_no_colab_markers.py | 74 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_no_colab_markers.py | 154 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_no_colab_markers.py | 156 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_no_colab_markers.py | 192 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_no_colab_markers.py | 194 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 66 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 68 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 78 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 80 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 88 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 90 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 109 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 111 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 118 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 120 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 174 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 177 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 195 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 197 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 215 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_generation_parity.py | 218 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_dependency_parity.py | 285 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_dependency_parity.py | 287 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 51 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 53 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 69 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 71 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 148 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 150 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 236 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_dependency_parity.py | 238 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_manifest.py | 62 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_manifest.py | 64 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_manifest.py | 280 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_manifest.py | 282 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_manifest.py | 43 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_manifest.py | 45 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_marimo_validity.py | 46 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_marimo_validity.py | 48 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_marimo_validity.py | 61 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_marimo_validity.py | 63 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_marimo_validity.py | 71 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_marimo_validity.py | 73 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_marimo_validity.py | 83 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_marimo_validity.py | 85 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_marimo_validity.py | 180 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_marimo_validity.py | 182 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_readme_links.py | 368 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_molab_readme_links.py | 370 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_readme_links.py | 55 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_molab_readme_links.py | 57 | # --------------------------------------------------------------------------- | COMMENT |
| 100 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | molab/Granite4.0_350M.py | 230 | CODE | |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 137 | CODE | |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 139 | CODE | |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 224 | CODE | |
| LOW | molab/Gemma4_(E2B)-Text.py | 229 | CODE | |
| LOW | molab/Qwen3_6_MoE.py | 162 | CODE | |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 477 | CODE | |
| LOW | molab/Gemma4_(12B)_Text.py | 230 | CODE | |
| LOW | molab/Gemma3_(270M)_Phone_Deployment.py | 49 | CODE | |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 137 | CODE | |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 221 | CODE | |
| LOW | molab/Granite4.0.py | 223 | CODE | |
| LOW | molab/Deepseek_OCR_2_(3B).py | 345 | CODE | |
| LOW | molab/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 125 | CODE | |
| LOW | molab/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 567 | CODE | |
| LOW | molab/Sesame_CSM_(1B)-TTS.py | 163 | CODE | |
| LOW | molab/Sesame_CSM_(1B)-TTS.py | 164 | CODE | |
| LOW | molab/Synthetic_Data_Hackathon.py | 143 | CODE | |
| LOW | molab/Synthetic_Data_Hackathon.py | 145 | CODE | |
| LOW | molab/Qwen3_VL_(8B)-Vision-GRPO.py | 121 | CODE | |
| LOW | molab/Gemma4_(E4B)-Text.py | 230 | CODE | |
| LOW | molab/Qwen3_5_(2B)_Vision.py | 213 | CODE | |
| LOW | molab/Gemma4_(E4B)-Audio.py | 112 | CODE | |
| LOW | molab/Gemma4_(E4B)-Audio.py | 179 | CODE | |
| LOW | molab/Gemma4_(E4B)-Audio.py | 192 | CODE | |
| LOW | molab/Gemma4_(12B)_Vision.py | 218 | CODE | |
| LOW | molab/Openenv_wordle_grpo.py | 134 | CODE | |
| LOW | molab/Spark_TTS_(0_5B).py | 48 | CODE | |
| LOW | molab/Spark_TTS_(0_5B).py | 205 | CODE | |
| LOW | molab/Spark_TTS_(0_5B).py | 207 | CODE | |
| LOW | molab/Spark_TTS_(0_5B).py | 420 | CODE | |
| LOW | molab/Spark_TTS_(0_5B).py | 420 | CODE | |
| LOW | molab/Qwen3_5_(4B)_Vision_GRPO.py | 115 | CODE | |
| LOW | molab/Gemma3_(4B)-Vision.py | 211 | CODE | |
| LOW | …CodeForces-cot-Finetune_for_Reasoning_on_CodeForces.py | 221 | CODE | |
| LOW | molab/Gemma4_(12B)_Audio.py | 180 | CODE | |
| LOW | molab/Gemma4_(12B)_Audio.py | 193 | CODE | |
| LOW | molab/gpt_oss_(20B)_500K_Context_Fine_tuning.py | 228 | CODE | |
| LOW | molab/LFM2.5_(1.2B)-Translation.py | 268 | CODE | |
| LOW | molab/Qwen3_5_(4B)_Vision.py | 213 | CODE | |
| LOW | molab/GPT_OSS_MXFP4_(20B)-Inference.py | 108 | CODE | |
| LOW | molab/Qwen3_MoE.py | 109 | CODE | |
| LOW | molab/Llama3_(8B)-ORPO.py | 100 | CODE | |
| LOW | molab/gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 100 | CODE | |
| LOW | molab/gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 158 | CODE | |
| LOW | molab/Zephyr_(7B)-DPO.py | 109 | CODE | |
| LOW | molab/Zephyr_(7B)-DPO.py | 428 | CODE | |
| LOW | molab/Ministral_3_VL_(3B)_Vision.py | 207 | CODE | |
| LOW | molab/Gemma3N_(4B)-Audio.py | 111 | CODE | |
| LOW | molab/Gemma3N_(4B)-Audio.py | 180 | CODE | |
| LOW | molab/Gemma3N_(4B)-Audio.py | 193 | CODE | |
| LOW | molab/Qwen3_5_(0_8B)_Vision.py | 213 | CODE | |
| LOW | molab/Mistral_v0.3_(7B)-CPT.py | 280 | CODE | |
| LOW | molab/Gemma4_(31B)-Vision.py | 218 | CODE | |
| LOW | molab/Whisper.py | 210 | CODE | |
| LOW | molab/Gemma3N_(2B)-Inference.py | 222 | CODE | |
| LOW | molab/Gemma3N_(2B)-Inference.py | 222 | CODE | |
| LOW | molab/bert_classification.py | 103 | CODE | |
| LOW | molab/Qwen3_VL_(8B)-Vision.py | 210 | CODE | |
| LOW | molab/LFM2.5_(1.2B)-Text_Completion.py | 237 | CODE | |
| 403 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | update_max_seq_length.py | 93 | except Exception as e: | CODE |
| MEDIUM | update_max_seq_length.py | 94 | print(f"Error reading {notebook_path}: {e}") | CODE |
| LOW | update_max_seq_length.py | 126 | except Exception as e: | CODE |
| LOW | replace_text.py | 20 | except Exception: | CODE |
| LOW | replace_text.py | 30 | except Exception: | CODE |
| LOW | replace_text.py | 76 | except Exception as e: | CODE |
| MEDIUM⚡ | update_all_notebooks.py | 4393 | print(f"Error: Notebook not found at {notebook_path}") | CODE |
| MEDIUM⚡ | update_all_notebooks.py | 4395 | print(f"Error: Invalid JSON in notebook at {notebook_path}") | CODE |
| MEDIUM⚡ | update_all_notebooks.py | 5415 | print(f"Error: README file '{readme_path}' not found.") | CODE |
| MEDIUM⚡ | update_all_notebooks.py | 5417 | print(f"Error processing README: {ve}") | CODE |
| MEDIUM⚡ | update_all_notebooks.py | 5419 | print(f"An error occurred while updating {readme_path}: {e}") | CODE |
| MEDIUM | update_all_notebooks.py | 4852 | print(f"Error processing {notebook_name}: {e}") | CODE |
| MEDIUM | update_all_notebooks.py | 1693 | def _validate_vllm_install_usage(notebook_path): | CODE |
| MEDIUM | update_all_notebooks.py | 2464 | def _split_pip_args(arg_string): | CODE |
| MEDIUM | update_all_notebooks.py | 3487 | def _safe_int(v): | CODE |
| MEDIUM | update_all_notebooks.py | 5705 | def _apply_global_fixes(nb_path): | CODE |
| LOW⚡ | update_all_notebooks.py | 4396 | except Exception as e: | CODE |
| LOW⚡ | update_all_notebooks.py | 5418 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 44 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 50 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 156 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 1379 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 1406 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 1425 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 1556 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 2032 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 2678 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 2926 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 3471 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 3482 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 3660 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 3766 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 4550 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 4560 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 4626 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 4663 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 4770 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 4851 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 5180 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 5184 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 5543 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 5701 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 5737 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 5838 | except Exception as e: | CODE |
| LOW | update_all_notebooks.py | 5998 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 6016 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 6119 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 6141 | except Exception: | CODE |
| LOW | update_all_notebooks.py | 6165 | except Exception as _molab_exc: # noqa: BLE001 - keep molab failures non-fatal | CODE |
| LOW | update_all_notebooks.py | 3394 | except Exception as e: | STRING |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 623 | except Exception as e: | STRING |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 634 | except Exception as e: | STRING |
| LOW | …nEnv_gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 858 | except Exception as e: | STRING |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 316 | except Exception: | STRING |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 447 | except Exception as e: | STRING |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 528 | except Exception as e: | STRING |
| LOW | molab/FunctionGemma_(270M).py | 535 | except Exception: | STRING |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 620 | except Exception as e: | STRING |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 631 | except Exception as e: | STRING |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 855 | except Exception as e: | STRING |
| 299 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | update_all_notebooks.py | 226 | # If you're not in Colab, just use pip install or uv pip install | COMMENT |
| LOW | update_all_notebooks.py | 236 | # If you're not in Colab, just use pip install! | COMMENT |
| LOW | update_all_notebooks.py | 291 | # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | molab/Llama3_(8B)-Ollama.py | 572 | [Unsloth](https://github.com/unslothai/unsloth) now allows you to automatically finetune and create a [Modelfile](ht | CODE |
| LOW | python_scripts/HuggingFace Course-Qwen2_5_7B_VL_GRPO.py | 39 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/HuggingFace Course-Qwen2_5_7B_VL_GRPO.py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| LOW | python_scripts/LFM2.5_(1.2B)-GRPO.py | 37 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/LFM2.5_(1.2B)-GRPO.py | 48 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/LFM2.5_(1.2B)-GRPO.py | 300 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/LFM2.5_(1.2B)-GRPO.py | 300 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| LOW | python_scripts/HuggingFace Course-Qwen2.5_(3B)-GRPO.py | 39 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/HuggingFace Course-Qwen2.5_(3B)-GRPO.py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/HuggingFace Course-Qwen2.5_(3B)-GRPO.py | 102 | # We directly leverage [@willccbb](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb) for data prep and | COMMENT |
| LOW | python_scripts/HuggingFace Course-Qwen3_8B_FP8_GRPO.py | 39 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/HuggingFace Course-Qwen3_8B_FP8_GRPO.py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/HuggingFace Course-Qwen3_8B_FP8_GRPO.py | 391 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/HuggingFace Course-Qwen3_8B_FP8_GRPO.py | 391 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | …scripts/Kaggle-Qwen3_(14B)-Reasoning-Conversational.py | 100 | # 2. We also leverage [Maxime Labonne's FineTome-100k](https://huggingface.co/datasets/mlabonne/FineTome-100k) dataset i | COMMENT |
| MEDIUM | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 156 | # Our dataset is a HuggingFace `Dataset` object, so we can leverage the abstraction's advantage to do a train-test split | COMMENT |
| LOW | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 226 | # Here we show both, but you could just use `context`. | COMMENT |
| LOW | python_scripts/Llama_FP8_GRPO.py | 37 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/Llama_FP8_GRPO.py | 48 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/Llama_FP8_GRPO.py | 388 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/Llama_FP8_GRPO.py | 388 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/Synthetic_Data_Hackathon.py | 74 | # This cell performs comprehensive data processing: | COMMENT |
| MEDIUM | python_scripts/Kaggle-Phi_4_(14B)-GRPO.py | 74 | # We directly leverage [@willccbb](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb) for data prep and | COMMENT |
| LOW | …n_scripts/HuggingFace Course-Mistral_v0.3_(7B)-GRPO.py | 39 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | …n_scripts/HuggingFace Course-Mistral_v0.3_(7B)-GRPO.py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | …n_scripts/HuggingFace Course-Mistral_v0.3_(7B)-GRPO.py | 102 | # We directly leverage [@willccbb](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb) for data prep and | COMMENT |
| LOW | python_scripts/Meta_Synthetic_Data_Llama3_2_(3B).py | 39 | # get_ipython().run_cell_magic('capture', '', 'import os\n!pip install --upgrade -qqq uv\nif "COLAB_" not in "".join(os. | COMMENT |
| LOW | python_scripts/Meta_Synthetic_Data_Llama3_2_(3B).py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| LOW | python_scripts/Qwen2_5_7B_VL_GRPO.py | 37 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/Qwen2_5_7B_VL_GRPO.py | 48 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/AMD-Llama3.1_(8B)-GRPO.py | 92 | # We directly leverage [@willccbb](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb) for data prep and | COMMENT |
| MEDIUM | …n_scripts/Qwen3_(32B)_A100-Reasoning-Conversational.py | 100 | # 2. We also leverage [Maxime Labonne's FineTome-100k](https://huggingface.co/datasets/mlabonne/FineTome-100k) dataset i | COMMENT |
| MEDIUM | python_scripts/Kaggle-Qwen3_(4B)-GRPO.py | 292 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/Kaggle-Qwen3_(4B)-GRPO.py | 292 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| LOW | python_scripts/Gemma4_(E2B)_GRPO.py | 31 | # # If you're not in Colab, just use pip install! | COMMENT |
| LOW | python_scripts/HuggingFace Course-Llama3.1_(8B)-GRPO.py | 39 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/HuggingFace Course-Llama3.1_(8B)-GRPO.py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/HuggingFace Course-Llama3.1_(8B)-GRPO.py | 102 | # We directly leverage [@willccbb](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb) for data prep and | COMMENT |
| MEDIUM | python_scripts/Qwen3_(14B).py | 100 | # 2. We also leverage [Maxime Labonne's FineTome-100k](https://huggingface.co/datasets/mlabonne/FineTome-100k) dataset i | COMMENT |
| MEDIUM | python_scripts/AMD-LFM2.5_(1.2B)-GRPO.py | 286 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/AMD-LFM2.5_(1.2B)-GRPO.py | 286 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/AMD-Mistral_v0.3_(7B)-GRPO.py | 92 | # We directly leverage [@willccbb](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb) for data prep and | COMMENT |
| MEDIUM | python_scripts/Kaggle-Llama_FP8_GRPO.py | 365 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/Kaggle-Llama_FP8_GRPO.py | 365 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| LOW | python_scripts/Qwen3_5_(4B)_Vision_GRPO.py | 45 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/Kaggle-Llama3_(8B)-Ollama.py | 405 | # [Unsloth](https://github.com/unslothai/unsloth) now allows you to automatically finetune and create a [Modelfile](http | COMMENT |
| MEDIUM | python_scripts/Kaggle-Llama3_(8B)-Ollama.py | 405 | # [Unsloth](https://github.com/unslothai/unsloth) now allows you to automatically finetune and create a [Modelfile](http | COMMENT |
| LOW | …cripts/HuggingFace Course-Qwen3_VL_(8B)-Vision-GRPO.py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/AMD-Llama_FP8_GRPO.py | 380 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/AMD-Llama_FP8_GRPO.py | 380 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| LOW | python_scripts/HuggingFace Course-Qwen3_(4B)-GRPO.py | 39 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| LOW | python_scripts/HuggingFace Course-Qwen3_(4B)-GRPO.py | 50 | # # If you're not in Colab, just use pip install! | COMMENT |
| MEDIUM | python_scripts/HuggingFace Course-Qwen3_(4B)-GRPO.py | 317 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/HuggingFace Course-Qwen3_(4B)-GRPO.py | 317 | # We're using Hugging Face's [Open R1 Math dataset](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed). Yo | COMMENT |
| MEDIUM | python_scripts/Llama3.2_(1B)-RAFT.py | 155 | # Our dataset is a HuggingFace `Dataset` object, so we can leverage the abstraction's advantage to do a train-test split | COMMENT |
| LOW | python_scripts/Llama3.2_(1B)-RAFT.py | 225 | # Here we show both, but you could just use `context`. | COMMENT |
| LOW | python_scripts/Gemma3_(4B)-Vision-GRPO.py | 37 | # get_ipython().run_cell_magic('capture', '', 'import os\nos.environ["UNSLOTH_VLLM_STANDBY"] = "1" # [NEW] Extra 30% con | COMMENT |
| 85 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | update_max_seq_length.py | 59 | def update_max_seq_length_in_source(source): | CODE |
| LOW⚡ | update_all_notebooks.py | 5424 | def copy_and_update_notebooks( | CODE |
| LOW | update_all_notebooks.py | 137 | def build_qat_native_install_block( | CODE |
| LOW | update_all_notebooks.py | 165 | def update_or_append_pip_install(base_content, package_name, new_install_line): | CODE |
| LOW | update_all_notebooks.py | 1262 | def _should_skip_readme_notebook(path): | CODE |
| LOW | update_all_notebooks.py | 1311 | def _file_has_trailing_newline(filepath): | CODE |
| LOW | update_all_notebooks.py | 1383 | def _restore_original_outputs(filepath): | CODE |
| LOW | update_all_notebooks.py | 1410 | def _normalize_lgpl_blank_line(filepath): | CODE |
| LOW | update_all_notebooks.py | 1654 | def _adjacent_install_like_code_cells(cells, first_code_idx): | CODE |
| LOW | update_all_notebooks.py | 1669 | def _is_residual_non_amd_install_cell(cells, idx, source_text): | CODE |
| LOW | update_all_notebooks.py | 1685 | def _is_stale_amd_announcement(source_text): | CODE |
| LOW | update_all_notebooks.py | 1693 | def _validate_vllm_install_usage(notebook_path): | CODE |
| LOW | update_all_notebooks.py | 1726 | def _assert_vllm_install_usage_or_fast_inference(notebook_files, max_workers=1, executor_type="process"): | CODE |
| LOW | update_all_notebooks.py | 1758 | def _validate_amd_install_package_parity(amd_notebook_path): | CODE |
| LOW | update_all_notebooks.py | 1797 | def _assert_amd_install_package_parity(notebook_files, max_workers=1, executor_type="process"): | CODE |
| LOW | update_all_notebooks.py | 1826 | def _validate_amd_install_runtime(notebook_path): | CODE |
| LOW | update_all_notebooks.py | 1883 | def _assert_amd_install_runtime(notebook_files, max_workers=1, executor_type="process"): | CODE |
| LOW | update_all_notebooks.py | 1908 | def _get_base_name_from_filename(filename): | CODE |
| LOW | update_all_notebooks.py | 1960 | def _strip_extra_trailing_blank_lines(lines): | CODE |
| LOW | update_all_notebooks.py | 2454 | def _iter_pip_install_arg_strings(text): | CODE |
| LOW | update_all_notebooks.py | 2471 | def _package_key_from_install_token(token): | CODE |
| LOW | update_all_notebooks.py | 2513 | def _extract_install_package_groups(text): | CODE |
| LOW | update_all_notebooks.py | 2591 | def _extract_install_package_names_from_text(text): | CODE |
| LOW | update_all_notebooks.py | 2628 | def _extract_preserved_setup_lines(text): | CODE |
| LOW | update_all_notebooks.py | 2668 | def _build_qat_version_vars_block(): | CODE |
| LOW | update_all_notebooks.py | 2717 | def _compose_amd_installation(notebook_path, source_install_texts): | CODE |
| LOW | update_all_notebooks.py | 2829 | def _prepend_missing_stdlib_imports(cell_text): | CODE |
| LOW | update_all_notebooks.py | 2852 | def _append_missing_amd_install_groups(new_install_text, source_install_text): | CODE |
| LOW | update_all_notebooks.py | 2893 | def extract_model_info_refined(filename, architecture_mapping, known_types_ordered): | CODE |
| LOW | update_all_notebooks.py | 3518 | def refresh_model_created_cache(notebook_paths, cache_path=_MODEL_CREATED_CACHE_PATH): | CODE |
| LOW | update_all_notebooks.py | 4510 | def _should_fallback_process_error(exc): | CODE |
| LOW | update_all_notebooks.py | 4531 | def _can_use_process_executor(): | CODE |
| LOW | update_all_notebooks.py | 5098 | def _make_section_row_sort_key(section_name): | CODE |
| LOW | update_all_notebooks.py | 5511 | def copy_and_update_amd_notebooks( | CODE |
| LOW | update_all_notebooks.py | 5609 | def convert_notebook_to_script(notebook_path: str, output_path: str): | CODE |
| LOW | update_all_notebooks.py | 5684 | def _ensure_memory_stats_hidden(nb_path): | CODE |
| LOW | update_all_notebooks.py | 3185 | def notebook_uses_fast_inference(notebook_path): | STRING |
| LOW | update_all_notebooks.py | 3292 | def extract_hf_model_refs_from_notebook(notebook_path): | STRING |
| LOW | update_all_notebooks.py | 3355 | def _load_model_created_cache(cache_path=_MODEL_CREATED_CACHE_PATH): | STRING |
| LOW | update_all_notebooks.py | 3399 | def _write_model_created_cache(cache, cache_path=_MODEL_CREATED_CACHE_PATH): | STRING |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 324 | def check_only_stdlib_imports(code: str): | STRING |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 454 | def create_locked_down_function(function): | STRING |
| LOW | molab/FunctionGemma_(270M).py | 466 | def prepare_messages_and_tools(example): | STRING |
| LOW | molab/Deepseek_OCR_2_(3B).py | 416 | def calculate_image_token_count( | CODE |
| LOW | molab/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 635 | def get_usd_to_euro_conversion_rate() -> float: | CODE |
| LOW | molab/Spark_TTS_(0_5B).py | 425 | def generate_speech_from_text( | STRING |
| LOW | molab/gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 160 | def _compress_and_merge_row_left(row: List[int]) -> Tuple[List[int], int, bool]: | STRING |
| LOW | molab/gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 332 | def _update_state_after_change(self) -> None: | STRING |
| LOW | molab/Gemma4_(E2B)_Reinforcement_Learning_2048_Game.py | 172 | def _compress_and_merge_row_left(row: List[int]) -> Tuple[List[int], int, bool]: | STRING |
| LOW | molab/Gemma4_(E2B)_Reinforcement_Learning_2048_Game.py | 344 | def _update_state_after_change(self) -> None: | STRING |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 332 | def check_only_stdlib_imports(code: str): | STRING |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 462 | def create_locked_down_function(function): | STRING |
| LOW | molab/Deepseek_OCR_(3B)-Evaluation.py | 535 | def calculate_image_token_count( | CODE |
| LOW | molab/Deepseek_OCR_(3B).py | 416 | def calculate_image_token_count( | CODE |
| LOW | …ss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.py | 147 | def _compress_and_merge_row_left(row: List[int]) -> Tuple[List[int], int, bool]: | STRING |
| LOW | …ss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.py | 319 | def _update_state_after_change(self) -> None: | STRING |
| LOW | molab/Oute_TTS_(1B).py | 256 | def create_speaker_representation(self, audio_bytes: bytes, transcript: str): | STRING |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 137 | def _compress_and_merge_row_left(row: List[int]) -> Tuple[List[int], int, bool]: | STRING |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 309 | def _update_state_after_change(self) -> None: | STRING |
| LOW | molab/gpt-oss-(20B)_A100-GRPO.py | 332 | def check_only_stdlib_imports(code: str): | STRING |
| 233 more matches not shown… | ||||
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| LOW | update_all_notebooks.py | 1297 | CODE | |
| LOW | update_all_notebooks.py | 1551 | CODE | |
| LOW | update_all_notebooks.py | 1908 | CODE | |
| LOW | update_all_notebooks.py | 1967 | CODE | |
| LOW | update_all_notebooks.py | 2027 | CODE | |
| LOW | update_all_notebooks.py | 2591 | CODE | |
| LOW | update_all_notebooks.py | 2628 | CODE | |
| LOW | update_all_notebooks.py | 2893 | CODE | |
| LOW | update_all_notebooks.py | 3292 | CODE | |
| LOW | update_all_notebooks.py | 3355 | CODE | |
| LOW | update_all_notebooks.py | 3791 | CODE | |
| LOW | update_all_notebooks.py | 4636 | CODE | |
| LOW | update_all_notebooks.py | 4751 | CODE | |
| LOW | update_all_notebooks.py | 5637 | CODE | |
| LOW | update_all_notebooks.py | 5684 | CODE | |
| LOW | update_all_notebooks.py | 5745 | CODE | |
| LOW | update_all_notebooks.py | 2182 | CODE | |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 288 | CODE | |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 476 | CODE | |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 734 | CODE | |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 295 | CODE | |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 741 | CODE | |
| LOW | molab/gpt_oss_(20B)_GRPO_BF16.py | 512 | CODE | |
| LOW | molab/NeMo-Gym-Multi-Environment.py | 165 | CODE | |
| LOW | molab/FunctionGemma_(270M).py | 458 | CODE | |
| LOW | molab/FunctionGemma_(270M).py | 466 | CODE | |
| LOW | molab/Deepseek_OCR_2_(3B).py | 337 | CODE | |
| LOW | molab/Deepseek_OCR_2_(3B).py | 518 | CODE | |
| LOW | molab/Synthetic_Data_Hackathon.py | 64 | CODE | |
| LOW | molab/Llasa_TTS_(1B).py | 187 | CODE | |
| LOW | molab/Llasa_TTS_(1B).py | 201 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 151 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 502 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 686 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 505 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 555 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 689 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 189 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 206 | CODE | |
| LOW | …)_Reinforcement_Learning_GRPO_Minesweeper_Game_BF16.py | 320 | CODE | |
| LOW | molab/NeMo-Gym-Sudoku.py | 159 | CODE | |
| LOW | molab/Zephyr_(7B)-DPO.py | 126 | CODE | |
| LOW | molab/Zephyr_(7B)-DPO.py | 137 | CODE | |
| LOW | molab/Zephyr_(7B)-DPO.py | 249 | CODE | |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 165 | CODE | |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 711 | CODE | |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 187 | CODE | |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 722 | CODE | |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 286 | CODE | |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 296 | CODE | |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 484 | CODE | |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 742 | CODE | |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 303 | CODE | |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 749 | CODE | |
| LOW | molab/gpt-oss-(20B)-GRPO.py | 520 | CODE | |
| LOW | molab/ERNIE_4_5_VL_28B_A3B_PT_Vision.py | 354 | CODE | |
| LOW | molab/ERNIE_4_5_VL_28B_A3B_PT_Vision.py | 377 | CODE | |
| LOW | molab/Deepseek_OCR_(3B)-Evaluation.py | 454 | CODE | |
| LOW | molab/Deepseek_OCR_(3B)-Evaluation.py | 640 | CODE | |
| LOW | molab/Deepseek_OCR_(3B).py | 337 | CODE | |
| 194 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | molab/gpt_oss_(20B)_GRPO_BF16.py | 233 | # Kernel generated by GPT-5 | STRING |
| HIGH | molab/gpt_oss_(20B)_GRPO_BF16.py | 381 | For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT | CODE |
| HIGH | molab/gpt-oss-(20B)-GRPO.py | 241 | # Kernel generated by GPT-5 | STRING |
| HIGH | molab/gpt-oss-(20B)-GRPO.py | 389 | For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT | CODE |
| HIGH | molab/gpt-oss-(20B)_A100-GRPO.py | 241 | # Kernel generated by GPT-5 | STRING |
| HIGH | molab/gpt-oss-(20B)_A100-GRPO.py | 389 | For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT | CODE |
| HIGH | python_scripts/gpt_oss_(20B)_GRPO_BF16.py | 137 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/gpt_oss_(20B)_GRPO_BF16.py | 261 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-gpt-oss-(20B)_A100-GRPO.py | 135 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-gpt-oss-(20B)_A100-GRPO.py | 259 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Gemma4_(E2B)_GRPO.py | 157 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Gemma4_(E2B)_GRPO.py | 281 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Kaggle-gpt-oss-(20B)_A100-GRPO.py | 139 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Kaggle-gpt-oss-(20B)_A100-GRPO.py | 263 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Kaggle-gpt-oss-(20B)-GRPO.py | 139 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Kaggle-gpt-oss-(20B)-GRPO.py | 263 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-Gemma4_(E2B)_GRPO.py | 144 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-Gemma4_(E2B)_GRPO.py | 268 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | …_scripts/HuggingFace Course-gpt-oss-(20B)_A100-GRPO.py | 139 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | …_scripts/HuggingFace Course-gpt-oss-(20B)_A100-GRPO.py | 263 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Kaggle-gpt_oss_(20B)_GRPO_BF16.py | 137 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/Kaggle-gpt_oss_(20B)_GRPO_BF16.py | 261 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/HuggingFace Course-gpt-oss-(20B)-GRPO.py | 139 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/HuggingFace Course-gpt-oss-(20B)-GRPO.py | 263 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/gpt-oss-(20B)-GRPO.py | 139 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/gpt-oss-(20B)-GRPO.py | 263 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | …_scripts/HuggingFace Course-gpt_oss_(20B)_GRPO_BF16.py | 139 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | …_scripts/HuggingFace Course-gpt_oss_(20B)_GRPO_BF16.py | 263 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/gpt-oss-(20B)_A100-GRPO.py | 139 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/gpt-oss-(20B)_A100-GRPO.py | 263 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-gpt_oss_(20B)_GRPO_BF16.py | 144 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-gpt_oss_(20B)_GRPO_BF16.py | 268 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-gpt-oss-(20B)-GRPO.py | 135 | # Kernel generated by GPT-5 | COMMENT |
| HIGH | python_scripts/AMD-gpt-oss-(20B)-GRPO.py | 259 | # For example, let's call `check_only_stdlib_imports` on a random piece of matrix multiplication code generated by GPT-5 | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | python_scripts/Kaggle-gpt-oss-(20B)-Fine-tuning.py | 166 | # The `HuggingFaceH4/Multilingual-Thinking` dataset will be utilized as our example. This dataset, available on Hugging | COMMENT |
| MEDIUM⚡ | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 50 | # This cookbook aims to show how to use Unsloth to use retrieval augmented finetuning (RAFT). Supervised finetuning is l | COMMENT |
| MEDIUM⚡ | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 52 | # RAFT differs from this in that it is an open-book exam format of finetuning! We allow the LLM to see not just the ques | COMMENT |
| MEDIUM⚡ | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 54 | # > Reference: [RAFT: Adapting Language Model to Domain Specific RAG](https://arxiv.org/abs/2403.10131) | COMMENT |
| MEDIUM | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 68 | # Next, we'll set up LlamaIndex. This involves configuring the language model (LLM) and embedding model that LlamaIndex | COMMENT |
| MEDIUM | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 86 | # We'll use the following code to download a research paper and then load it using `SimpleDirectoryReader`. This will be | COMMENT |
| MEDIUM | python_scripts/AMD-Llama3.2_(1B)-RAFT.py | 209 | # We need to put everything together into a single 'text' field for the LLM to be trained on. According to the [RAFT pap | COMMENT |
| MEDIUM | python_scripts/gpt-oss-(20B)-Fine-tuning.py | 166 | # The `HuggingFaceH4/Multilingual-Thinking` dataset will be utilized as our example. This dataset, available on Hugging | COMMENT |
| MEDIUM | python_scripts/Openenv_wordle_grpo.py | 168 | # This function orchestrates the interaction between the model and the Wordle environment. For each prompt in the batch, | COMMENT |
| MEDIUM | python_scripts/gpt-oss-(120B)_A100-Fine-tuning.py | 166 | # The `HuggingFaceH4/Multilingual-Thinking` dataset will be utilized as our example. This dataset, available on Hugging | COMMENT |
| MEDIUM⚡ | python_scripts/Llama3.2_(1B)-RAFT.py | 49 | # This cookbook aims to show how to use Unsloth to use retrieval augmented finetuning (RAFT). Supervised finetuning is l | COMMENT |
| MEDIUM⚡ | python_scripts/Llama3.2_(1B)-RAFT.py | 51 | # RAFT differs from this in that it is an open-book exam format of finetuning! We allow the LLM to see not just the ques | COMMENT |
| MEDIUM⚡ | python_scripts/Llama3.2_(1B)-RAFT.py | 53 | # > Reference: [RAFT: Adapting Language Model to Domain Specific RAG](https://arxiv.org/abs/2403.10131) | COMMENT |
| MEDIUM | python_scripts/Llama3.2_(1B)-RAFT.py | 67 | # Next, we'll set up LlamaIndex. This involves configuring the language model (LLM) and embedding model that LlamaIndex | COMMENT |
| MEDIUM | python_scripts/Llama3.2_(1B)-RAFT.py | 85 | # We'll use the following code to download a research paper and then load it using `SimpleDirectoryReader`. This will be | COMMENT |
| MEDIUM | python_scripts/Llama3.2_(1B)-RAFT.py | 208 | # We need to put everything together into a single 'text' field for the LLM to be trained on. According to the [RAFT pap | COMMENT |
| MEDIUM | python_scripts/AMD-gpt-oss-(120B)_A100-Fine-tuning.py | 173 | # The `HuggingFaceH4/Multilingual-Thinking` dataset will be utilized as our example. This dataset, available on Hugging | COMMENT |
| MEDIUM | python_scripts/AMD-gpt-oss-(20B)-Fine-tuning.py | 173 | # The `HuggingFaceH4/Multilingual-Thinking` dataset will be utilized as our example. This dataset, available on Hugging | COMMENT |
| MEDIUM | python_scripts/AMD-Openenv_wordle_grpo.py | 165 | # This function orchestrates the interaction between the model and the Wordle environment. For each prompt in the batch, | COMMENT |
| MEDIUM⚡ | python_scripts/Kaggle-Llama3.2_(1B)-RAFT.py | 49 | # This cookbook aims to show how to use Unsloth to use retrieval augmented finetuning (RAFT). Supervised finetuning is l | COMMENT |
| MEDIUM⚡ | python_scripts/Kaggle-Llama3.2_(1B)-RAFT.py | 51 | # RAFT differs from this in that it is an open-book exam format of finetuning! We allow the LLM to see not just the ques | COMMENT |
| MEDIUM⚡ | python_scripts/Kaggle-Llama3.2_(1B)-RAFT.py | 53 | # > Reference: [RAFT: Adapting Language Model to Domain Specific RAG](https://arxiv.org/abs/2403.10131) | COMMENT |
| MEDIUM | python_scripts/Kaggle-Llama3.2_(1B)-RAFT.py | 67 | # Next, we'll set up LlamaIndex. This involves configuring the language model (LLM) and embedding model that LlamaIndex | COMMENT |
| MEDIUM | python_scripts/Kaggle-Llama3.2_(1B)-RAFT.py | 85 | # We'll use the following code to download a research paper and then load it using `SimpleDirectoryReader`. This will be | COMMENT |
| MEDIUM | python_scripts/Kaggle-Llama3.2_(1B)-RAFT.py | 208 | # We need to put everything together into a single 'text' field for the LLM to be trained on. According to the [RAFT pap | COMMENT |
| MEDIUM | …thon_scripts/Kaggle-gpt-oss-(120B)_A100-Fine-tuning.py | 166 | # The `HuggingFaceH4/Multilingual-Thinking` dataset will be utilized as our example. This dataset, available on Hugging | COMMENT |
| MEDIUM | scripts/molab_dependencies.py | 446 | # scaffolding (``import os, re``, the ``if "COLAB_" ...`` | COMMENT |
| MEDIUM | scripts/molab_dependencies.py | 793 | # scaffolding-line entries (``import os, re``, ``if "COLAB_" ...``) | COMMENT |
| MEDIUM | scripts/molab_dependencies.py | 810 | # get_dropped_deps from reporting scaffolding tokens as dropped dependencies. | COMMENT |
| MEDIUM | scripts/scan_packages.py | 181 | # Container / orchestration abuse | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | python_scripts/NeMo-Gym-Multi-Environment.py | 49 | # In this example, we will do full finetuning, but Unsloth supports optimized low precision (e.g. 4 or 8 bit) or paramet | COMMENT |
| HIGH | python_scripts/NeMo-Gym-Multi-Environment.py | 440 | # In this example, we will train the model using Group Relative Policy Optimization (GRPO), an efficient and effective r | COMMENT |
| HIGH | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 33 | # In this example, we will do full finetuning, but Unsloth supports optimized low precision (e.g. 4 or 8 bit) or paramet | COMMENT |
| HIGH | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 424 | # In this example, we will train the model using Group Relative Policy Optimization (GRPO), an efficient and effective r | COMMENT |
| HIGH | python_scripts/Openenv_wordle_grpo.py | 86 | # In this example, we'll connect to the hosted environment at [openenv/wordle](https://huggingface.co/spaces/openenv/wor | COMMENT |
| HIGH | python_scripts/AMD-bert_classification.py | 124 | # We now use the [Emotion dataset](https://huggingface.co/datasets/dair-ai/emotion) from `dair-ai`, which contains text | COMMENT |
| HIGH | python_scripts/NeMo-Gym-Sudoku.py | 47 | # In this example, we will do full finetuning, but Unsloth supports optimized low precision (e.g. 4 or 8 bit) or paramet | COMMENT |
| HIGH | python_scripts/NeMo-Gym-Sudoku.py | 381 | # In this example, we will train the model using Group Relative Policy Optimization (GRPO), an efficient and effective r | COMMENT |
| HIGH | python_scripts/bert_classification.py | 117 | # We now use the [Emotion dataset](https://huggingface.co/datasets/dair-ai/emotion) from `dair-ai`, which contains text | COMMENT |
| HIGH | python_scripts/AMD-Openenv_wordle_grpo.py | 83 | # In this example, we'll connect to the hosted environment at [openenv/wordle](https://huggingface.co/spaces/openenv/wor | COMMENT |
| HIGH | python_scripts/AMD-NeMo-Gym-Sudoku.py | 33 | # In this example, we will do full finetuning, but Unsloth supports optimized low precision (e.g. 4 or 8 bit) or paramet | COMMENT |
| HIGH | python_scripts/AMD-NeMo-Gym-Sudoku.py | 367 | # In this example, we will train the model using Group Relative Policy Optimization (GRPO), an efficient and effective r | COMMENT |
| HIGH | python_scripts/Kaggle-bert_classification.py | 117 | # We now use the [Emotion dataset](https://huggingface.co/datasets/dair-ai/emotion) from `dair-ai`, which contains text | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | molab/Qwen3_VL_(8B)-Vision-GRPO.py | 248 | # Define the delimiter variables for clarity and easy modification | STRING |
| MEDIUM | molab/Qwen3_5_(4B)_Vision_GRPO.py | 241 | # Define the delimiter variables for clarity and easy modification | STRING |
| MEDIUM | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 335 | # Create an easy puzzle | STRING |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 339 | # Create an easy puzzle | STRING |
| MEDIUM | molab/Oute_TTS_(1B).py | 258 | Creates a v3-compatible speaker dictionary using Whisper and AudioProcessor. # Create a dummy ModelConfig m | CODE |
| MEDIUM | python_scripts/HuggingFace Course-Qwen2_5_7B_VL_GRPO.py | 173 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/Kaggle-Qwen3_VL_(8B)-Vision-GRPO.py | 151 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/Qwen3_VL_(8B)-Vision-GRPO.py | 151 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/AMD-Qwen3_5_(4B)_Vision_GRPO.py | 159 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/Qwen2_5_7B_VL_GRPO.py | 171 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/Qwen3_5_(4B)_Vision_GRPO.py | 166 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | …cripts/HuggingFace Course-Qwen3_VL_(8B)-Vision-GRPO.py | 176 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/Gemma3_(4B)-Vision-GRPO.py | 196 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 298 | # Create an easy puzzle | COMMENT |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 459 | # Create the prompt that instructs the model to generate a Sudoku solving strategy. You can customize this to some other | STRING |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 673 | # Create the training dataset. | COMMENT |
| MEDIUM | python_scripts/AMD-Qwen2_5_7B_VL_GRPO.py | 163 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 291 | # Create an easy puzzle | COMMENT |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 452 | # Create the prompt that instructs the model to generate a Sudoku solving strategy. You can customize this to some other | STRING |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 666 | # Create the training dataset. | COMMENT |
| MEDIUM | python_scripts/AMD-Qwen3_VL_(8B)-Vision-GRPO.py | 166 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | …pts/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 280 | # Create an easy puzzle | COMMENT |
| MEDIUM | …pts/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 441 | # Create the prompt that instructs the model to generate a Sudoku solving strategy. You can customize this to some other | STRING |
| MEDIUM | …pts/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 659 | # Create the training dataset. | COMMENT |
| MEDIUM | …AMD-Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 284 | # Create an easy puzzle | COMMENT |
| MEDIUM | …AMD-Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 445 | # Create the prompt that instructs the model to generate a Sudoku solving strategy. You can customize this to some other | STRING |
| MEDIUM | …AMD-Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 663 | # Create the training dataset. | COMMENT |
| MEDIUM | python_scripts/AMD-Gemma3_(4B)-Vision-GRPO.py | 188 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/Kaggle-Qwen2_5_7B_VL_GRPO.py | 148 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 277 | # Create an easy puzzle | COMMENT |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 438 | # Create the prompt that instructs the model to generate a Sudoku solving strategy. You can customize this to some other | STRING |
| MEDIUM | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 652 | # Create the training dataset. | COMMENT |
| MEDIUM | python_scripts/Oute_TTS_(1B).py | 147 | # Create a dummy ModelConfig mainly for device and paths needed by AudioProcessor/DacInterface | COMMENT |
| MEDIUM | python_scripts/Kaggle-Gemma3_(4B)-Vision-GRPO.py | 173 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | …_scripts/HuggingFace Course-Gemma3_(4B)-Vision-GRPO.py | 198 | # Define the delimiter variables for clarity and easy modification | COMMENT |
| MEDIUM | python_scripts/Kaggle-Oute_TTS_(1B).py | 147 | # Create a dummy ModelConfig mainly for device and paths needed by AudioProcessor/DacInterface | COMMENT |
| MEDIUM | python_scripts/AMD-Oute_TTS_(1B).py | 149 | # Create a dummy ModelConfig mainly for device and paths needed by AudioProcessor/DacInterface | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | update_max_seq_length.py | 108 | # Check if this cell contains trainer code AND dataset_kwargs with skip_prepare_dataset | COMMENT |
| LOW | update_max_seq_length.py | 110 | # Check if max_seq_length exists in this cell | COMMENT |
| LOW | update_all_notebooks.py | 1984 | # Check if this line continues (ends with backslash) | COMMENT |
| LOW | update_all_notebooks.py | 4311 | # Check if the last cell already contains footer content using key markers | COMMENT |
| LOW | update_all_notebooks.py | 4322 | # Check if notebook has partial footer content but missing LGPL line | COMMENT |
| LOW | molab/Deepseek_OCR_2_(3B).py | 653 | } # Check if this is the assistant's turn # This is the split point. All tokens added *so far* # are part | CODE |
| LOW | molab/Whisper.py | 171 | # Set this to the language you want to train on | STRING |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 288 | RESET = "\x1b[0m" # Check if placement is valid | CODE |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 303 | ): # Check if puzzle is complete | CODE |
| LOW | molab/Deepseek_OCR_(3B)-Evaluation.py | 772 | } # Check if this is the assistant's turn # This is the split point. All tokens added *so far* # are part | CODE |
| LOW | molab/Deepseek_OCR_(3B).py | 656 | } # Check if this is the assistant's turn # This is the split point. All tokens added *so far* # are part | CODE |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 292 | RESET = "\x1b[0m" # Check if placement is valid | CODE |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 307 | ): # Check if puzzle is complete | CODE |
| LOW | molab/Oute_TTS_(1B).py | 558 | continue # Check if penalties should be applied | STRING |
| LOW | molab/Deepseek_OCR_(3B)-Eval.py | 656 | } # Check if this is the assistant's turn # This is the split point. All tokens added *so far* # are part | CODE |
| LOW | python_scripts/Kaggle-Deepseek_OCR_(3B).py | 422 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/Deepseek_OCR_2_(3B).py | 422 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/AMD-Deepseek_OCR_(3B)-Evaluation.py | 564 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/Meta_Synthetic_Data_Llama3_2_(3B).py | 99 | # Check if it succeeded: | COMMENT |
| LOW | python_scripts/AMD-Meta_Synthetic_Data_Llama3_2_(3B).py | 87 | # Check if it succeeded: | COMMENT |
| LOW | …on_scripts/Kaggle-Meta_Synthetic_Data_Llama3_2_(3B).py | 74 | # Check if it succeeded: | COMMENT |
| LOW | python_scripts/Kaggle-Whisper.py | 106 | #Set this to the language you want to train on | COMMENT |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 230 | # Check if placement is valid | COMMENT |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 243 | # Check if puzzle is complete | COMMENT |
| LOW | python_scripts/AMD-Whisper.py | 113 | #Set this to the language you want to train on | COMMENT |
| LOW | python_scripts/Kaggle-Deepseek_OCR_(3B)-Eval.py | 422 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/AMD-Deepseek_OCR_(3B)-Eval.py | 429 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/Kaggle-Deepseek_OCR_2_(3B).py | 422 | # Check if this is the assistant's turn | COMMENT |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 223 | # Check if placement is valid | COMMENT |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 236 | # Check if puzzle is complete | COMMENT |
| LOW | python_scripts/Whisper.py | 106 | #Set this to the language you want to train on | COMMENT |
| LOW | …pts/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 212 | # Check if placement is valid | COMMENT |
| LOW | …pts/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 225 | # Check if puzzle is complete | COMMENT |
| LOW | …AMD-Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 216 | # Check if placement is valid | COMMENT |
| LOW | …AMD-Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 229 | # Check if puzzle is complete | COMMENT |
| LOW | python_scripts/Deepseek_OCR_(3B)-Evaluation.py | 557 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/Deepseek_OCR_(3B).py | 422 | # Check if this is the assistant's turn | COMMENT |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 209 | # Check if placement is valid | COMMENT |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 222 | # Check if puzzle is complete | COMMENT |
| LOW | python_scripts/Oute_TTS_(1B).py | 438 | # Check if penalties should be applied | COMMENT |
| LOW | python_scripts/AMD-Deepseek_OCR_2_(3B).py | 429 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/AMD-Deepseek_OCR_(3B).py | 429 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/Deepseek_OCR_(3B)-Eval.py | 422 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/Kaggle-Deepseek_OCR_(3B)-Evaluation.py | 557 | # Check if this is the assistant's turn | COMMENT |
| LOW | python_scripts/Kaggle-Oute_TTS_(1B).py | 438 | # Check if penalties should be applied | COMMENT |
| LOW | python_scripts/AMD-Oute_TTS_(1B).py | 440 | # Check if penalties should be applied | COMMENT |
| LOW | scripts/fix_templates.py | 48 | # Check if import torch already exists | COMMENT |
| LOW | scripts/fix_templates.py | 65 | # Check if already has Version check | COMMENT |
| LOW | scripts/scan_packages.py | 1939 | # Check if any are git deps | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 181 | # Step 1: Clone NeMo Gym | STRING |
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 189 | # Step 2: Create venv and install dependencies | STRING |
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 210 | # Step 3: Create sudoku dataset | STRING |
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 229 | # Step 4: Download instruction_following dataset | STRING |
| LOW | molab/NeMo-Gym-Multi-Environment.py | 246 | # Step 5: Create resources_only.yaml for instruction_following if missing | STRING |
| LOW⚡ | molab/NeMo-Gym-Sudoku.py | 175 | # Step 1: Clone NeMo Gym | STRING |
| LOW⚡ | molab/NeMo-Gym-Sudoku.py | 183 | # Step 2: Create venv and install dependencies | STRING |
| LOW⚡ | molab/NeMo-Gym-Sudoku.py | 204 | # Step 3: Create dataset | STRING |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 126 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 134 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 151 | # Step 3: Create sudoku dataset | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 168 | # Step 4: Download instruction_following dataset | COMMENT |
| LOW | python_scripts/NeMo-Gym-Multi-Environment.py | 185 | # Step 5: Create resources_only.yaml for instruction_following if missing | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 110 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 118 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 135 | # Step 3: Create sudoku dataset | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 152 | # Step 4: Download instruction_following dataset | COMMENT |
| LOW | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 169 | # Step 5: Create resources_only.yaml for instruction_following if missing | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Sudoku.py | 120 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Sudoku.py | 128 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Sudoku.py | 145 | # Step 3: Create dataset | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Sudoku.py | 106 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Sudoku.py | 114 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Sudoku.py | 131 | # Step 3: Create dataset | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 181 | # Step 1: Clone NeMo Gym | STRING |
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 189 | # Step 2: Create venv and install dependencies | STRING |
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 210 | # Step 3: Create sudoku dataset | STRING |
| LOW⚡ | molab/NeMo-Gym-Multi-Environment.py | 229 | # Step 4: Download instruction_following dataset | STRING |
| LOW | molab/NeMo-Gym-Multi-Environment.py | 246 | # Step 5: Create resources_only.yaml for instruction_following if missing | STRING |
| LOW⚡ | molab/NeMo-Gym-Sudoku.py | 175 | # Step 1: Clone NeMo Gym | STRING |
| LOW⚡ | molab/NeMo-Gym-Sudoku.py | 183 | # Step 2: Create venv and install dependencies | STRING |
| LOW⚡ | molab/NeMo-Gym-Sudoku.py | 204 | # Step 3: Create dataset | STRING |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 126 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 134 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 151 | # Step 3: Create sudoku dataset | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Multi-Environment.py | 168 | # Step 4: Download instruction_following dataset | COMMENT |
| LOW | python_scripts/NeMo-Gym-Multi-Environment.py | 185 | # Step 5: Create resources_only.yaml for instruction_following if missing | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 110 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 118 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 135 | # Step 3: Create sudoku dataset | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 152 | # Step 4: Download instruction_following dataset | COMMENT |
| LOW | python_scripts/AMD-NeMo-Gym-Multi-Environment.py | 169 | # Step 5: Create resources_only.yaml for instruction_following if missing | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Sudoku.py | 120 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Sudoku.py | 128 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/NeMo-Gym-Sudoku.py | 145 | # Step 3: Create dataset | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Sudoku.py | 106 | # Step 1: Clone NeMo Gym | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Sudoku.py | 114 | # Step 2: Create venv and install dependencies | COMMENT |
| LOW⚡ | python_scripts/AMD-NeMo-Gym-Sudoku.py | 131 | # Step 3: Create dataset | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | molab/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 463 | CODE | |
| LOW | python_scripts/AMD-Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 366 | CODE | |
| LOW | python_scripts/HuggingFace Course-Qwen2.5_(3B)-GRPO.py | 150 | CODE | |
| LOW | python_scripts/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 359 | CODE | |
| LOW | python_scripts/Kaggle-Phi_4_(14B)-GRPO.py | 122 | CODE | |
| LOW | …n_scripts/HuggingFace Course-Mistral_v0.3_(7B)-GRPO.py | 150 | CODE | |
| LOW | python_scripts/AMD-Llama3.1_(8B)-GRPO.py | 140 | CODE | |
| LOW | python_scripts/HuggingFace Course-Llama3.1_(8B)-GRPO.py | 150 | CODE | |
| LOW | python_scripts/AMD-Mistral_v0.3_(7B)-GRPO.py | 140 | CODE | |
| LOW | python_scripts/Kaggle-Qwen2.5_(3B)-GRPO.py | 125 | CODE | |
| LOW | python_scripts/Kaggle-Mistral_v0.3_(7B)-GRPO.py | 125 | CODE | |
| LOW | …on_scripts/Kaggle-Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 359 | CODE | |
| LOW | python_scripts/Llama3.1_(8B)-GRPO.py | 148 | CODE | |
| LOW | python_scripts/Kaggle-Llama3.1_(8B)-GRPO.py | 125 | CODE | |
| LOW | python_scripts/Qwen2.5_(3B)-GRPO.py | 148 | CODE | |
| LOW | python_scripts/AMD-Phi_4_(14B)-GRPO.py | 137 | CODE | |
| LOW | python_scripts/HuggingFace Course-Phi_4_(14B)-GRPO.py | 147 | CODE | |
| LOW | python_scripts/AMD-Qwen2.5_(3B)-GRPO.py | 140 | CODE | |
| LOW | python_scripts/Mistral_v0.3_(7B)-GRPO.py | 148 | CODE | |
| LOW | python_scripts/Phi_4_(14B)-GRPO.py | 145 | CODE | |
| LOW | scripts/molab_generate.py | 615 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | molab/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 253 | Performs element-wise addition of two numerical vectors. Both vectors must be of the same length and contain n | STRING |
| HIGH | python_scripts/AMD-Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 181 | Performs element-wise addition of two numerical vectors. Both vectors must be of the same length and contain n | STRING |
| HIGH | python_scripts/Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 174 | Performs element-wise addition of two numerical vectors. Both vectors must be of the same length and contain n | STRING |
| HIGH | …on_scripts/Kaggle-Qwen2.5_Coder_(1.5B)-Tool_Calling.py | 174 | Performs element-wise addition of two numerical vectors. Both vectors must be of the same length and contain n | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | molab/gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 332 | def _update_state_after_change(self) -> None: | STRING |
| LOW | …lab/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 276 | def _update_state(self) -> None: | CODE |
| LOW | molab/Gemma4_(E2B)_Reinforcement_Learning_2048_Game.py | 344 | def _update_state_after_change(self) -> None: | STRING |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 280 | def _update_state(self) -> None: | CODE |
| LOW | …ss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.py | 319 | def _update_state_after_change(self) -> None: | STRING |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 309 | def _update_state_after_change(self) -> None: | STRING |
| LOW | …s/AMD-Gemma4_(E2B)_Reinforcement_Learning_2048_Game.py | 251 | def _update_state_after_change(self) -> None: | CODE |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 225 | def _update_state_after_change(self) -> None: | CODE |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 241 | def _update_state(self) -> None: | CODE |
| LOW | …ipts/gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 229 | def _update_state_after_change(self) -> None: | CODE |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 234 | def _update_state(self) -> None: | CODE |
| LOW | …pts/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 223 | def _update_state(self) -> None: | CODE |
| LOW | …ripts/Gemma4_(E2B)_Reinforcement_Learning_2048_Game.py | 247 | def _update_state_after_change(self) -> None: | CODE |
| LOW | …AMD-Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.py | 227 | def _update_state(self) -> None: | CODE |
| LOW | …/AMD-gpt_oss_(20B)_Reinforcement_Learning_2048_Game.py | 229 | def _update_state_after_change(self) -> None: | CODE |
| LOW | …ss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.py | 229 | def _update_state_after_change(self) -> None: | CODE |
| LOW | …Ministral_3_(3B)_Reinforcement_Learning_Sudoku_Game.py | 220 | def _update_state(self) -> None: | CODE |
| LOW | …ss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.py | 222 | def _update_state_after_change(self) -> None: | CODE |
| LOW | …gpt_oss_(20B)_Reinforcement_Learning_2048_Game_BF16.py | 218 | def _update_state_after_change(self) -> None: | CODE |
| LOW | scripts/scan_packages.py | 1878 | def update_req_file(filepath: str, updates: dict[int, str]) -> None: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | python_scripts/Kaggle-Llama3.2_(11B)-Vision.py | 145 | # We will craft an custom instruction asking the VLM to be an expert radiographer. Notice also instead of just 1 instruc | COMMENT |
| MEDIUM | python_scripts/AMD-Llama3.2_(11B)-Vision.py | 152 | # We will craft an custom instruction asking the VLM to be an expert radiographer. Notice also instead of just 1 instruc | COMMENT |
| MEDIUM | python_scripts/Llama3.2_(11B)-Vision.py | 145 | # We will craft an custom instruction asking the VLM to be an expert radiographer. Notice also instead of just 1 instruc | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | molab/Whisper.py | 394 | # Example usage | STRING |
| LOW | python_scripts/Kaggle-Whisper.py | 293 | # Example usage | COMMENT |
| LOW | python_scripts/AMD-Whisper.py | 300 | # Example usage | COMMENT |
| LOW | python_scripts/Whisper.py | 293 | # Example usage | COMMENT |