《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调(全参数/Lora)、部署国内外开源大模型(LLM)/多模态大模型(MLLM)教程
This report summarizes scanner evidence for datawhalechina/self-llm, a Jupyter Notebook project with 32,656 GitHub stars. SynthScan examined 107,884 lines of code across 409 source files, recording 252 pattern matches distributed across 15 syntactic categories. The legacy adjusted pattern signal is 4.0 (Low pattern signal); it is not an authorship estimate.
Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.
Use each vector to guide manual verification of the underlying findings.
Payload schema: 1.0.0 · Engine: 2.0.0 · Scoring: heuristic-density-v1 · Scan date: 2026-10-31.
Can maintainers explain intent, assumptions, and trade-offs? 64 finding(s).
Are imports declared and package/API names verified? 35 finding(s).
Are wrappers, guards, and repeated structures necessary? 167 finding(s).
Which changes need focused human review? 252 finding(s).
This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.
Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.
This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.
The scanner identified 252 distinct pattern matches across 15 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. 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 configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | models/ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/InternLM/06-InternLM接入LangChain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/Qwen/07-Qwen-7B-Chat 接入langchain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/Yi/02-Yi-6B-Chat 接入langchain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答 案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | …ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手/run_gradio.py | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答 案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/InternLM/06-InternLM接入LangChain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答 案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | …s/InternLM/06-InternLM接入LangChain搭建知识库助手/run_gradio.py | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答 案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答 案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/Qwen/07-Qwen-7B-Chat 接入langchain搭建知识库助手.md | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答 案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | …/Qwen/07-Qwen-7B-Chat 接入langchain搭建知识库助手/run_gradio.py | 0 | 使用以下上下文来回答最后的问题。如果你不知道答案,就说你不知道,不要试图编造答 案。尽量使答案简明扼要。总是在回答的最后说“谢谢你的提问!”。 {context} 问题: {question} 有用的回答: | STRING |
| HIGH | models/ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手.md | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | …ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手/run_gradio.py | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | models/InternLM/06-InternLM接入LangChain搭建知识库助手.md | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | …s/InternLM/06-InternLM接入LangChain搭建知识库助手/run_gradio.py | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | models/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手.md | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | …/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手/run_gradio.py | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | models/Qwen/07-Qwen-7B-Chat 接入langchain搭建知识库助手.md | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | …/Qwen/07-Qwen-7B-Chat 接入langchain搭建知识库助手/run_gradio.py | 0 | 提醒:<br> 1. 初始化数据库时间可能较长,请耐心等待。 2. 使用中如果出现异常,将会在文本输入框进行展示,请不要惊慌。 <br> | STRING |
| HIGH | models/Gemma3/04-Gemma3-4b evalscope智商情商评测.md | 0 | 以下为多个ai服务的api端点地址,用于配置任务: - siliconflow: https://api.siliconflow.cn/v1/chat/completions - dashscope: https://dashscope.a | STRING |
| HIGH | models/Gemma4/04-Gemma4-E4B-it evalscope智商情商评测.md | 0 | 以下为多个ai服务的api端点地址,用于配置任务: - siliconflow: https://api.siliconflow.cn/v1/chat/completions - dashscope: https://dashscope.a | STRING |
| HIGH | models/Qwen3/04-Qwen3-8B EvalScope智商情商评测.md | 0 | 以下为多个ai服务的api端点地址,用于配置任务: - siliconflow: https://api.siliconflow.cn/v1/chat/completions - dashscope: https://dashscope.a | STRING |
| HIGH | …3B-Instruct/04-Hunyuan-A13B-Instruct EvalScope 并发测试.md | 0 | 以下为多个ai服务的api端点地址,用于配置任务: - siliconflow: https://api.siliconflow.cn/v1/chat/completions - dashscope: https://dashscope.a | STRING |
| HIGH | models/Gemma3/6-gemma3-4B-itGRPO微调及通过swanlab可视化.md | 0 | you are given a problem. think about the problem and provide your working out. place it between {reasoning_start} and {r | STRING |
| HIGH | models/Gemma4/6-gemma4-E4B-itGRPO微调及通过swanlab可视化.md | 0 | you are given a problem. think about the problem and provide your working out. place it between {reasoning_start} and {r | STRING |
| HIGH | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 0 | you are given a problem. think about the problem and provide your working out. place it between {reasoning_start} and {r | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | utils.py | 124 | print(f"Error: {data['message']}") | CODE |
| LOW | models/Llama4/01-Llama4-对话助手/01-Llama4-对话助手.md | 277 | except Exception as e: | CODE |
| LOW | models/Llama4/01-Llama4-对话助手/01-Llama4-对话助手.md | 291 | except Exception as e: | CODE |
| MEDIUM | models/Llama4/01-Llama4-对话助手/01-Llama4-对话助手.md | 217 | def generate(): | CODE |
| MEDIUM | models/Llama4/01-Llama4-对话助手/01-Llama4-对话助手.md | 281 | def clear_history(): | CODE |
| LOW | models/Llama4/01-Llama4-对话助手/app/app.py | 129 | except Exception as e: | CODE |
| LOW | models/Llama4/01-Llama4-对话助手/app/app.py | 143 | except Exception as e: | CODE |
| MEDIUM | models/Llama4/01-Llama4-对话助手/app/app.py | 69 | def generate(): | CODE |
| MEDIUM | models/Llama4/01-Llama4-对话助手/app/app.py | 133 | def clear_history(): | CODE |
| LOW | models/Qwen3-VL/02-Qwen3-VL-4B-Instruct FastApi 部署调用.md | 188 | except Exception as e: | CODE |
| LOW | models/Qwen3-VL/02-Qwen3-VL-4B-Instruct FastApi 部署调用.md | 255 | except Exception as e: | CODE |
| LOW | models/Qwen3-VL/02-Qwen3-VL-4B-Instruct FastApi 部署调用.md | 294 | except Exception as e: | CODE |
| LOW | models/Qwen3-VL/02-Qwen3-VL-4B-Instruct FastApi 部署调用.md | 345 | except Exception as e: | CODE |
| LOW | models/Qwen3-VL/02-Qwen3-VL-4B-Instruct FastApi 部署调用.md | 535 | except Exception as e: | CODE |
| LOW | models/Qwen3-VL/02-Qwen3-VL-4B-Instruct FastApi 部署调用.md | 599 | except Exception as e: | CODE |
| LOW | models/Qwen3-VL/02-Qwen3-VL-4B-Instruct FastApi 部署调用.md | 650 | except Exception as e: | CODE |
| LOW | …VL/05-Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 725 | except Exception: | CODE |
| LOW | …VL/05-Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 824 | except Exception: | CODE |
| LOW | …VL/05-Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 836 | except Exception: | CODE |
| LOW | …VL/05-Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 838 | except Exception as e: | CODE |
| LOW | …n3-VL/Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 706 | except Exception: | CODE |
| LOW | …n3-VL/Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 805 | except Exception: | CODE |
| LOW | …n3-VL/Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 817 | except Exception: | CODE |
| LOW | …n3-VL/Qwen3-VL-4B-Instruct Lora 可视化微调案例 - LaTexOCR.md | 819 | except Exception as e: | CODE |
| LOW | …L-4B-Instruct FastApi 参考代码/api_server_qwen3vl_video.py | 126 | except Exception as e: | CODE |
| LOW | …1-Qwen3-VL-4B-Instruct FastApi 参考代码/test_simple_api.py | 25 | except Exception as e: | CODE |
| LOW | …1-Qwen3-VL-4B-Instruct FastApi 参考代码/test_simple_api.py | 64 | except Exception as e: | CODE |
| LOW | …1-Qwen3-VL-4B-Instruct FastApi 参考代码/test_simple_api.py | 115 | except Exception as e: | CODE |
| LOW | …01-Qwen3-VL-4B-Instruct FastApi 参考代码/test_video_api.py | 28 | except Exception as e: | CODE |
| LOW | …01-Qwen3-VL-4B-Instruct FastApi 参考代码/test_video_api.py | 79 | except Exception as e: | CODE |
| LOW | …-4B-Instruct FastApi 参考代码/api_server_qwen3vl_simple.py | 125 | except Exception as e: | CODE |
| LOW | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 63 | except Exception: | CODE |
| LOW | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 162 | except Exception: | CODE |
| LOW | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 174 | except Exception: | CODE |
| LOW | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 176 | except Exception as e: | CODE |
| LOW | models/gpt-oss/4-gpt-oss-20b Lora 微调及 SwanLab 可视化记录.md | 245 | except Exception as e: | CODE |
| LOW | models/gpt-oss/3-gpt-oss-20b lmstudio 本地部署调用.md | 130 | except Exception as exc: | CODE |
| LOW | models/ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手.md | 398 | except Exception as e: | CODE |
| LOW | models/ChatGLM/Extra-ChatGLM3-6B-Pipeline.md | 341 | except Exception as e: | CODE |
| LOW | models/ChatGLM/Extra-ChatGLM3-6B-Pipeline.md | 404 | except Exception as e: | CODE |
| LOW | models/ChatGLM/Extra-ChatGLM3-6B-Pipeline.md | 457 | except Exception as e: | CODE |
| LOW | models/ChatGLM/Extra-ChatGLM3-6B-Pipeline.md | 491 | except Exception as e: | CODE |
| LOW | …ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手/run_gradio.py | 71 | except Exception as e: | CODE |
| LOW | models/InternLM/06-InternLM接入LangChain搭建知识库助手.md | 401 | except Exception as e: | CODE |
| LOW | …s/InternLM/06-InternLM接入LangChain搭建知识库助手/run_gradio.py | 61 | except Exception as e: | CODE |
| LOW | …VL/02-Qwen2-VL-2B-Instruct Web Demo 参考代码/mm_qwen2vl.py | 167 | except Exception: | CODE |
| LOW | models/Qwen2.5/06-Qwen2.5-7B-Instruct o1-like 推理链实现.md | 118 | except Exception as e: | CODE |
| LOW | models/Gemma3/8-gemma3-4b-it 模型服务部署.md | 86 | except Exception as e: | CODE |
| LOW | models/Gemma3/01-gemma-3-4b-it FastApi 部署调用.md | 136 | except Exception as e: | CODE |
| LOW | models/Gemma3/01-gemma-3-4b-it FastApi 部署调用.md | 146 | except Exception as e: | CODE |
| LOW | models/Gemma3/01-gemma-3-4b-it FastApi 部署调用.md | 210 | except Exception as e: | CODE |
| LOW | models/Atom/02-Atom-7B-Chat Lora 微调.md | 298 | except Exception as e: | CODE |
| LOW | models/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手.md | 443 | except Exception as e: | CODE |
| LOW | …/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手/run_gradio.py | 60 | except Exception as e: | CODE |
| LOW | models/Atom/02-Atom-7B-Chat-Lora/train.py | 215 | except Exception as e: | CODE |
| LOW | models/Gemma4/01-gemma-4-E4B-it FastApi 部署调用.md | 164 | except Exception as e: | CODE |
| LOW | models/Gemma4/01-gemma-4-E4B-it FastApi 部署调用.md | 174 | except Exception as e: | CODE |
| LOW | models/Gemma4/01-gemma-4-E4B-it FastApi 部署调用.md | 243 | except Exception: | CODE |
| LOW | models/Gemma4/01-gemma-4-E4B-it FastApi 部署调用.md | 256 | except Exception as e: | CODE |
| LOW | models/Gemma4/verify_gemma4_tutorials.py | 183 | except Exception: | CODE |
| 45 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 427 | # ======================== | COMMENT |
| MEDIUM | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 429 | # ======================== | COMMENT |
| MEDIUM | models_mlx/run_app_gradio.py | 20 | # ============================================================ | COMMENT |
| MEDIUM | models_mlx/run_app_gradio.py | 22 | # ============================================================ | COMMENT |
| MEDIUM⚡ | models_mlx/run_app_gradio.py | 131 | # ============================================================ | COMMENT |
| MEDIUM⚡ | models_mlx/run_app_gradio.py | 133 | # ============================================================ | COMMENT |
| MEDIUM | models_mlx/run_app_gradio.py | 307 | # ============================================================ | COMMENT |
| MEDIUM | models_mlx/run_app_gradio.py | 309 | # ============================================================ | COMMENT |
| MEDIUM | models_mlx/modules/framework.py | 104 | # ============================================================ | COMMENT |
| MEDIUM | models_mlx/modules/framework.py | 106 | # ============================================================ | COMMENT |
| MEDIUM⚡ | models_mlx/modules/download_model.py | 14 | # ============================================================ | COMMENT |
| MEDIUM⚡ | models_mlx/modules/download_model.py | 16 | # ============================================================ | COMMENT |
| MEDIUM⚡ | models_mlx/modules/download_model.py | 23 | # ============================================================ | COMMENT |
| MEDIUM⚡ | models_mlx/modules/download_model.py | 25 | # ============================================================ | COMMENT |
| MEDIUM | models_mlx/modules/download_model.py | 183 | # ============================================================ | COMMENT |
| MEDIUM | models_mlx/modules/download_model.py | 185 | # ============================================================ | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | utils.py | 2 | CODE | |
| LOW | utils.py | 3 | CODE | |
| LOW | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 2 | CODE | |
| LOW | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 3 | CODE | |
| LOW | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 3 | CODE | |
| LOW | …ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手/run_gradio.py | 15 | CODE | |
| LOW | …s/InternLM/06-InternLM接入LangChain搭建知识库助手/run_gradio.py | 5 | CODE | |
| LOW | …2B-Instruct FastApi 参考代码/api_server_image_and_video.py | 3 | CODE | |
| LOW | …-Qwen2-VL-2B-Instruct FastApi 参考代码/api_server_image.py | 3 | CODE | |
| LOW | …-Instruct FastApi 参考代码/qwen_vl_utils/vision_process.py | 1 | CODE | |
| LOW | …/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手/run_gradio.py | 5 | CODE | |
| LOW | models/Atom/02-Atom-7B-Chat-Lora/train.py | 15 | CODE | |
| LOW | models/Atom/02-Atom-7B-Chat-Lora/train.py | 18 | CODE | |
| LOW | models/Gemma4/api.py | 2 | CODE | |
| LOW | …dels/MiniCPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/trainer.py | 5 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 2 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 5 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 8 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 8 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 9 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 9 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 16 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 16 | CODE | |
| LOW | models/MiniCPM/train.py | 6 | CODE | |
| LOW | models/Kimi-VL/01-Kimi-VL-对话助手/app/app.py | 9 | CODE | |
| LOW | …/Qwen/07-Qwen-7B-Chat 接入langchain搭建知识库助手/run_gradio.py | 5 | CODE | |
| LOW | models/XVERSE/code/LLM.py | 4 | CODE | |
| LOW | models/XVERSE/code/LLM.py | 4 | CODE | |
| LOW | models/XVERSE/code/model_download.py | 1 | CODE | |
| LOW | models/XVERSE/code/model_download.py | 2 | CODE | |
| LOW | models/XVERSE/code/model_download.py | 2 | CODE | |
| LOW | models/XVERSE/code/model_download.py | 3 | CODE | |
| LOW | models/BlueLM/04-BlueLM-7B-Chat Lora 微调.py | 3 | CODE | |
| LOW | examples/Chat-嬛嬛/train.py | 4 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | utils.py | 91 | CODE | |
| LOW | …/ChatGLM/05-ChatGLM3-6B接入LangChain搭建知识库助手/create_db.py | 23 | CODE | |
| LOW | …els/InternLM/06-InternLM接入LangChain搭建知识库助手/creat_db.py | 11 | CODE | |
| LOW | …-Instruct FastApi 参考代码/qwen_vl_utils/vision_process.py | 82 | CODE | |
| LOW | …-Instruct FastApi 参考代码/qwen_vl_utils/vision_process.py | 303 | CODE | |
| LOW | …VL/02-Qwen2-VL-2B-Instruct Web Demo 参考代码/mm_qwen2vl.py | 54 | CODE | |
| LOW | …VL/02-Qwen2-VL-2B-Instruct Web Demo 参考代码/mm_qwen2vl.py | 229 | CODE | |
| LOW | …ls/Atom/03-Atom-7B-Chat 接入langchain搭建知识库助手/creat_db.py | 13 | CODE | |
| LOW | models/Gemma4/verify_gemma4_tutorials.py | 66 | CODE | |
| LOW | models/Gemma4/verify_gemma4_tutorials.py | 134 | CODE | |
| LOW | models/Gemma4/api.py | 107 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 231 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 271 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 310 | CODE | |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 427 | CODE | |
| LOW | models/Kimi-VL/01-Kimi-VL-对话助手/app/app.py | 167 | CODE | |
| LOW | …ls/Qwen/07-Qwen-7B-Chat 接入langchain搭建知识库助手/creat_db.py | 11 | CODE | |
| LOW | models_mlx/run_app_gradio.py | 329 | CODE | |
| LOW | models_mlx/modules/download_model.py | 120 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 717 | # Step 1: 构造初始输入并生成输出(不加载 LoRA) | COMMENT |
| LOW | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 738 | # Step 2: 保存 GRPO 微调得到的 LoRA 权重 | COMMENT |
| LOW | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 741 | # Step 3: 检查保存的 safetensors 权重不为全零 | COMMENT |
| LOW | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 752 | # Step 4: 构造消息格式输入并应用 tokenizer 的 chat_template | COMMENT |
| LOW | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 765 | # Step 5: 加载微调后的 LoRA 并生成输出 | COMMENT |
| LOW | examples/Chat-嬛嬛/readme.md | 15 | ## Step 1: 环境准备 | COMMENT |
| LOW | examples/Chat-嬛嬛/readme.md | 44 | ## Step 2: 数据准备 | COMMENT |
| LOW | examples/Chat-嬛嬛/readme.md | 130 | ## Step 3: 模型训练 | COMMENT |
| LOW | examples/AMchat-高等数学/readme.md | 26 | ### Step 1: 数据准备 | COMMENT |
| LOW | examples/AMchat-高等数学/readme.md | 49 | ### Step 2: 环境准备 | COMMENT |
| LOW | examples/AMchat-高等数学/readme.md | 66 | ### Step 3: 模型微调 | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | models/Gemma3/6-gemma3-4B-itGRPO微调及通过swanlab可视化.md | 258 | def match_format_approximately(completions, **kwargs): | CODE |
| LOW | models/Gemma4/verify_gemma4_tutorials.py | 66 | def test_fastapi_smoke_with_mock() -> bool: | CODE |
| LOW | models/Gemma4/6-gemma4-E4B-itGRPO微调及通过swanlab可视化.md | 260 | def match_format_approximately(completions, **kwargs): | CODE |
| LOW | models/phi4/06-Phi-4-GRPO及swanlab可视化.md | 229 | def strict_format_reward_func(completions, **kwargs) -> list[float]: | STRING |
| LOW | models/MiniCPM-o/04-MiniCPM-0-2.6 Lora微调.md | 259 | def make_supervised_data_module( | CODE |
| LOW | models/MiniCPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/train.py | 17 | def make_supervised_data_module( | CODE |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 199 | def conversation_to_ids_minicpm(conversation, tokenizer): | CODE |
| LOW | models/Qwen3/10-Qwen3-8B GRPO微调及通过swanlab可视化.md | 474 | def match_format_approximately(completions, **kwargs): | CODE |
| LOW | …n-A13B-Instruct/03-Hunyuan-A13B-Instruct-SGLang部署调用.md | 157 | def chatcompletionwiththinkbyargs(messages, enable_thinking=True): | CODE |
| LOW | …l-Qwen/05-DeepSeek-R1-0528-Qwen3-8B-GRPO及swanlab可视化.md | 198 | def match_format_approximately(completions, **kwargs): | CODE |
| LOW | …l-Qwen/05-DeepSeek-R1-0528-Qwen3-8B-GRPO及swanlab可视化.md | 287 | def format_and_language_reward_func(completions, **kwargs): | CODE |
| LOW | examples/数字生命/readme.md | 23 | def convert_to_sharegpt_format(original_data,new_system_value=None): | CODE |
| LOW | examples/Tianji-天机/readme.md | 225 | def extract_and_merge_conversations(folder_path, output_file): | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | models/GLM-4/04-GLM-4-9B-Chat vLLM 部署调用.md | 101 | # tokenizer = AutoTokenizer.from_pretrained(model, use_fast=False) # 加载分词器后传入vLLM 模型,但不是必要的。 | COMMENT |
| LOW | models/Qwen2.5/03-Qwen2.5-7B-Instruct vLLM 部署调用.md | 101 | COMMENT | |
| LOW | models/MiniCPM-o/03-MiniCPM-o-2.6 多模态语音能力.md | 141 | COMMENT | |
| LOW | models/Qwen2/04-Qwen2-7B-Instruct vLLM 部署调用.md | 121 | # tokenizer = AutoTokenizer.from_pretrained(model, use_fast=False) | COMMENT |
| LOW | models/Qwen/08-Qwen-7B-Chat Lora 低精度微调.py | 61 | tokenized_id = ds.map(process_func, remove_columns=ds.column_names) | COMMENT |
| LOW | models/Qwen1.5/07-Qwen1.5-7B-Chat vLLM 推理部署调用.md | 101 | if __name__ == "__main__": | COMMENT |
| LOW | models/XVERSE/code/data_format.py | 21 | with open('ruozhiba.json', 'w', encoding='utf-8') as f: | COMMENT |
| LOW | models/InternLM3/04-InternLM3-8B-Instruct LoRA.md | 201 | > 注意:此处要记得修改为自己的模型路径哦~ | COMMENT |
| LOW | models/InternLM3/04-InternLM3-8B-Instruct LoRA.md | 221 | # ) | COMMENT |
| LOW | …still-Qwen/04-DeepSeek-R1-Distill-Qwen-7B vLLM 部署调用.md | 101 | # tokenizer = AutoTokenizer.from_pretrained(model, use_fast=False) | COMMENT |
| LOW | examples/Tianji-天机/readme.md | 41 | from zhipuai import ZhipuAI | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | utils.py | 21 | # Read files | COMMENT |
| LOW | utils.py | 61 | # Check if the task contains "Lora" or "微调" (case-insensitive) | COMMENT |
| LOW | utils.py | 84 | # Print results | COMMENT |
| LOW | models/GLM-4/benchmark_throughput.py | 155 | # Check if we can add more requests to the batch. | COMMENT |
| LOW | models/Qwen2.5/benchmark_throughput.py | 257 | # Check if we can add more requests to the batch. | COMMENT |
| LOW | models/Qwen2/benchmark_throughput.py | 154 | # Check if we can add more requests to the batch. | COMMENT |
| LOW | models/Qwen1.5/benchmark_throughput.py | 154 | # Check if we can add more requests to the batch. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 162 | except Exception: | CODE |
| HIGH | …uct Lora 可视化微调案例 - LaTexOCR/compare_qwen3_vl_infer.py | 174 | except Exception: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …-Instruct FastApi 参考代码/qwen_vl_utils/vision_process.py | 132 | calculate the number of frames for video used for model inputs. Args: ele (dict): a dict contains the confi | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …dels/GLM-4.7-Flash/03-GLM-4.7-Flash-Lora微调及Docker镜像.md | 137 | swanlab.login(api_key='your-apikey', save=True) # 记得替换为自己账号的apikey | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …-Instruct FastApi 参考代码/qwen_vl_utils/vision_process.py | 22 | logger = logging.getLogger(__name__) | CODE |
| LOW | models/Gemma4/api.py | 17 | logger = logging.getLogger(__name__) | CODE |
| LOW | …CPM-o/04-MiniCPM-0-2.6 Lora微调 参考代码/minicpm_datasets.py | 19 | logger = logging.getLogger(__name__) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | utils.py | 149 | # Usage example | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | models/XVERSE/code/LLM.py | 30 | CODE |