huggingface/sentence-transformers

Pattern Findings

1959 matches across 12 categories. Click a row to expand file-level details.

Hyper-Verbose Identifiers850 hits · 796 pts

Severity	File	Line	Snippet
LOW	…entence_transformer/deprecated_model_card_templates.py	125	def model_card_get_pooling_function(pooling_mode):
LOW	sentence_transformers/sentence_transformer/model.py	926	def set_pooling_include_prompt(self, include_prompt: bool) -> None:
LOW	sentence_transformers/sentence_transformer/model.py	972	def get_sentence_embedding_dimension(self) -> int \| None:
LOW	sentence_transformers/sentence_transformer/model.py	1010	def truncate_sentence_embeddings(self, truncate_dim: int \| None) -> Iterator[None]:
LOW	…ntence_transformers/sentence_transformer/model_card.py	118	def get_model_specific_metadata(self) -> dict[str, Any]:
LOW	…sentence_transformer/losses/batch_semi_hard_triplet.py	110	def batch_semi_hard_triplet_loss(self, labels: Tensor, embeddings: Tensor) -> Tensor:
LOW	…tence_transformer/losses/multiple_negatives_ranking.py	235	def compute_loss_from_embeddings(self, embeddings: list[Tensor], labels: Tensor) -> Tensor:
LOW	…ence_transformers/sentence_transformer/losses/angle.py	83	def compute_loss_from_embeddings(
LOW	…ransformer/losses/cached_multiple_negatives_ranking.py	416	def calculate_loss_and_cache_gradients(self, reps: list[list[Tensor]]) -> Tensor:
LOW	…transformer/losses/global_orthogonal_regularization.py	139	def compute_loss_from_embeddings(
LOW	…mers/sentence_transformer/losses/batch_hard_triplet.py	228	def get_anchor_positive_triplet_mask(labels: Tensor) -> Tensor:
LOW	…mers/sentence_transformer/losses/batch_hard_triplet.py	247	def get_anchor_negative_triplet_mask(labels: Tensor) -> Tensor:
LOW	…transformers/sentence_transformer/losses/margin_mse.py	177	def compute_loss_from_embeddings(self, embeddings: list[Tensor], labels: Tensor) -> Tensor:
LOW	…rmers/sentence_transformer/losses/cosine_similarity.py	83	def compute_loss_from_embeddings(self, embeddings: list[Tensor], labels: Tensor) -> Tensor:
LOW	…nce_transformers/sentence_transformer/losses/cosent.py	86	def compute_loss_from_embeddings(self, embeddings: list[Tensor], labels: Tensor) -> Tensor:
LOW	…ce_transformers/sentence_transformer/losses/triplet.py	87	def compute_loss_from_embeddings(self, embeddings: list[Tensor], labels: Tensor) -> Tensor:
LOW	…e_transformer/losses/batch_hard_soft_margin_triplet.py	99	def batch_hard_triplet_soft_margin_loss(self, labels: Tensor, embeddings: Tensor) -> Tensor:
LOW	…sformers/sentence_transformer/losses/distill_kl_div.py	141	def compute_loss_from_embeddings(self, embeddings: list[Tensor], labels: Tensor) -> Tensor:
LOW	…rmers/sentence_transformer/losses/cached_gist_embed.py	278	def calculate_loss_and_cache_gradients(self, reps: list[list[Tensor]], reps_guided: list[list[Tensor]]) -> Tensor:
LOW	…nsformers/sentence_transformer/losses/embed_distill.py	196	def compute_loss_from_embeddings(self, embeddings: list[Tensor], teacher_embeddings: list[Tensor]) -> Tensor:
LOW	…ntence_transformer/evaluation/binary_classification.py	316	def find_best_acc_and_threshold(scores, labels, high_score_more_similar: bool):
LOW	…nsformers/sentence_transformer/evaluation/reranking.py	291	def compute_metrics_individual(self, model: SentenceTransformer):
LOW	…nsformers/sentence_transformer/evaluation/nano_beir.py	468	def _load_dataset_subset_split(self, subset: str, split: str, required_columns: list[str]):
LOW	…nsformers/sentence_transformer/evaluation/nano_beir.py	523	def store_metrics_in_model_card_data(self, args, *kwargs):
LOW	…e_transformers/sentence_transformer/modules/pooling.py	26	def _convert_legacy_pooling_kwargs(kwargs: dict[str, Any]) -> None:
LOW	…e_transformers/sentence_transformer/modules/pooling.py	46	def _deprecated_pooling_mode_kwargs(func):
LOW	…e_transformers/sentence_transformer/modules/pooling.py	151	def _exclude_prompt_from_mask(attention_mask: Tensor, prompt_length: int) -> Tensor:
LOW	…ransformers/sentence_transformer/modules/clip_model.py	36	def _get_default_modality_config(config: dict[str, Any]) -> tuple[ModalityConfig, str]:
LOW	sentence_transformers/util/deprecated_import.py	261	def setup_deprecated_module_imports() -> None:
LOW	sentence_transformers/util/similarity.py	299	def to_similarity_pairwise_fn(
LOW	sentence_transformers/util/retrieval.py	89	def paraphrase_mining_embeddings(
LOW	sentence_transformers/util/environment.py	28	def suggest_extra_on_exception() -> Generator[None, None, None]:
LOW	sentence_transformers/util/environment.py	72	def check_package_availability(package_name: str, owner: str) -> bool:
LOW	sentence_transformers/util/file_io.py	34	def is_sentence_transformer_model(
LOW	sentence_transformers/util/decorators.py	48	def transformer_kwargs_decorator(func):
LOW	sentence_transformers/util/decorators.py	92	def cross_encoder_init_args_decorator(func):
LOW	sentence_transformers/util/decorators.py	165	def cross_encoder_predict_rank_args_decorator(func):
LOW	sentence_transformers/util/decorators.py	190	def save_to_hub_args_decorator(func):
LOW	sentence_transformers/backend/optimize.py	19	def export_optimized_onnx_model(
LOW	sentence_transformers/backend/quantize.py	24	def export_dynamic_quantized_onnx_model(
LOW	sentence_transformers/backend/quantize.py	107	def export_static_quantized_openvino_model(
LOW	sentence_transformers/backend/utils.py	155	def save_or_push_to_hub_model(
LOW	sentence_transformers/cross_encoder/model.py	402	def get_default_activation_fn(self) -> Callable:
LOW	sentence_transformers/cross_encoder/model.py	463	def default_activation_function(self) -> Callable:
LOW	sentence_transformers/cross_encoder/fit_mixin.py	397	def smart_batching_collate_text_only(self, batch: list[InputExample]) -> BatchEncoding:
LOW	sentence_transformers/cross_encoder/model_card.py	269	def get_model_specific_metadata(self) -> dict[str, Any]:
LOW	…ss_encoder/losses/cached_multiple_negatives_ranking.py	239	def calculate_loss_and_cache_gradients(self, logits: list[Tensor], batch_size: int) -> Tensor:
LOW	…nce_transformers/cross_encoder/evaluation/nano_beir.py	389	def _load_dataset_subset_split(self, subset: str, split: str, required_columns: list[str]):
LOW	sentence_transformers/sparse_encoder/model.py	597	def set_pooling_include_prompt(self, include_prompt: bool) -> None:
LOW	sentence_transformers/sparse_encoder/model.py	825	def get_sentence_embedding_dimension(self) -> int \| None:
LOW	sentence_transformers/sparse_encoder/model.py	1110	def splade_pooling_chunk_size(self) -> int \| None:
LOW	sentence_transformers/sparse_encoder/model.py	1131	def splade_pooling_chunk_size(self, value: int \| None) -> None:
LOW	sentence_transformers/sparse_encoder/model_card.py	118	def get_model_specific_metadata(self) -> dict[str, Any]:
LOW	sentence_transformers/sparse_encoder/search_engines.py	160	def semantic_search_elasticsearch(
LOW	sentence_transformers/sparse_encoder/search_engines.py	428	def semantic_search_opensearch(
LOW	…ce_transformers/sparse_encoder/losses/cached_splade.py	182	def calculate_loss_and_cache_gradients(self, reps: list[list[Tensor]], labels: Tensor \| None) -> Tensor:
LOW	sentence_transformers/sparse_encoder/losses/flops.py	47	def compute_loss_from_embeddings(self, embeddings: torch.Tensor) -> torch.Tensor:
LOW	sentence_transformers/sparse_encoder/losses/csr.py	15	def normalized_mean_squared_error(reconstruction: torch.Tensor, original_input: torch.Tensor) -> torch.Tensor:
LOW	sentence_transformers/sparse_encoder/losses/csr.py	68	def compute_loss_from_embeddings(self, outputs: list[dict[str, torch.Tensor]]) -> dict[str, torch.Tensor]:
LOW	…arse_encoder/evaluation/sparse_embedding_similarity.py	159	def store_metrics_in_model_card_data(
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Unused Imports553 hits · 522 pts

Severity	File	Line
LOW	sentence_transformers/__init__.py	1
LOW	sentence_transformers/__init__.py	10
LOW	sentence_transformers/__init__.py	10
LOW	sentence_transformers/__init__.py	10
LOW	sentence_transformers/__init__.py	15
LOW	sentence_transformers/__init__.py	15
LOW	sentence_transformers/__init__.py	16
LOW	sentence_transformers/__init__.py	16
LOW	sentence_transformers/__init__.py	16
LOW	sentence_transformers/__init__.py	16
LOW	sentence_transformers/__init__.py	22
LOW	sentence_transformers/__init__.py	22
LOW	sentence_transformers/__init__.py	23
LOW	sentence_transformers/__init__.py	24
LOW	sentence_transformers/__init__.py	25
LOW	sentence_transformers/__init__.py	26
LOW	sentence_transformers/__init__.py	27
LOW	sentence_transformers/__init__.py	28
LOW	sentence_transformers/__init__.py	28
LOW	sentence_transformers/__init__.py	28
LOW	sentence_transformers/__init__.py	28
LOW	sentence_transformers/__init__.py	34
LOW	sentence_transformers/__init__.py	36
LOW	sentence_transformers/__init__.py	37
LOW	sentence_transformers/__init__.py	38
LOW	…entence_transformer/deprecated_model_card_templates.py	6
LOW	sentence_transformers/sentence_transformer/__init__.py	1
LOW	sentence_transformers/sentence_transformer/__init__.py	3
LOW	sentence_transformers/sentence_transformer/__init__.py	4
LOW	sentence_transformers/sentence_transformer/__init__.py	5
LOW	sentence_transformers/sentence_transformer/__init__.py	6
LOW	sentence_transformers/sentence_transformer/__init__.py	7
LOW	…nce_transformers/sentence_transformer/training_args.py	1
LOW	…nce_transformers/sentence_transformer/training_args.py	5
LOW	…nce_transformers/sentence_transformer/training_args.py	5
LOW	sentence_transformers/sentence_transformer/model.py	1
LOW	…nce_transformers/sentence_transformer/data_collator.py	1
LOW	sentence_transformers/sentence_transformer/trainer.py	1
LOW	sentence_transformers/sentence_transformer/fit_mixin.py	1
LOW	…ntence_transformers/sentence_transformer/model_card.py	1
LOW	…sentence_transformer/losses/batch_semi_hard_triplet.py	1
LOW	…/losses/cached_multiple_negatives_symmetric_ranking.py	1
LOW	…ntence_transformers/sentence_transformer/losses/mse.py	1
LOW	…tence_transformer/losses/multiple_negatives_ranking.py	1
LOW	…transformers/sentence_transformer/losses/gist_embed.py	1
LOW	…rmers/sentence_transformer/losses/batch_all_triplet.py	1
LOW	…ransformers/sentence_transformer/losses/contrastive.py	1
LOW	…ence_transformers/sentence_transformer/losses/angle.py	1
LOW	…ransformer/losses/cached_multiple_negatives_ranking.py	1
LOW	…transformer/losses/global_orthogonal_regularization.py	1
LOW	…mers/sentence_transformer/losses/batch_hard_triplet.py	1
LOW	…transformers/sentence_transformer/losses/margin_mse.py	1
LOW	…e_transformers/sentence_transformer/losses/__init__.py	2
LOW	…e_transformers/sentence_transformer/losses/__init__.py	4
LOW	…e_transformers/sentence_transformer/losses/__init__.py	6
LOW	…e_transformers/sentence_transformer/losses/__init__.py	7
LOW	…e_transformers/sentence_transformer/losses/__init__.py	8
LOW	…e_transformers/sentence_transformer/losses/__init__.py	9
LOW	…e_transformers/sentence_transformer/losses/__init__.py	10
LOW	…e_transformers/sentence_transformer/losses/__init__.py	10
493 more matches not shown…

Cross-File Repetition100 hits · 500 pts

Severity	File	Line	Snippet
HIGH	…sentence_transformer/losses/batch_semi_hard_triplet.py	0	@misc{hermans2017defense, title={in defense of the triplet loss for person re-identification}, author={alexander hermans
HIGH	…rmers/sentence_transformer/losses/batch_all_triplet.py	0	@misc{hermans2017defense, title={in defense of the triplet loss for person re-identification}, author={alexander hermans
HIGH	…mers/sentence_transformer/losses/batch_hard_triplet.py	0	@misc{hermans2017defense, title={in defense of the triplet loss for person re-identification}, author={alexander hermans
HIGH	…ce_transformers/sentence_transformer/losses/triplet.py	0	@misc{hermans2017defense, title={in defense of the triplet loss for person re-identification}, author={alexander hermans
HIGH	…e_transformer/losses/batch_hard_soft_margin_triplet.py	0	@misc{hermans2017defense, title={in defense of the triplet loss for person re-identification}, author={alexander hermans
HIGH	…ransformer/losses/cached_multiple_negatives_ranking.py	0	random-state context manager class. reference: https://github.com/luyug/gradcache. this class will back up the pytorch's
HIGH	…rmers/sentence_transformer/losses/cached_gist_embed.py	0	random-state context manager class. reference: https://github.com/luyug/gradcache. this class will back up the pytorch's
HIGH	…ss_encoder/losses/cached_multiple_negatives_ranking.py	0	random-state context manager class. reference: https://github.com/luyug/gradcache. this class will back up the pytorch's
HIGH	…ransformer/losses/cached_multiple_negatives_ranking.py	0	a backward hook to backpropagate the cached gradients mini-batch by mini-batch.
HIGH	…rmers/sentence_transformer/losses/cached_gist_embed.py	0	a backward hook to backpropagate the cached gradients mini-batch by mini-batch.
HIGH	…ss_encoder/losses/cached_multiple_negatives_ranking.py	0	a backward hook to backpropagate the cached gradients mini-batch by mini-batch.
HIGH	…ransformer/losses/cached_multiple_negatives_ranking.py	0	do forward pass on all the minibatches of the input features and yield corresponding embeddings.
HIGH	…rmers/sentence_transformer/losses/cached_gist_embed.py	0	do forward pass on all the minibatches of the input features and yield corresponding embeddings.
HIGH	…ss_encoder/losses/cached_multiple_negatives_ranking.py	0	do forward pass on all the minibatches of the input features and yield corresponding embeddings.
HIGH	…rs/sentence_transformer/datasets/parallel_sentences.py	0	this file contains deprecated code that can only be used with the old `model.fit`-style sentence transformers v2.x train
HIGH	…_transformers/sentence_transformer/readers/nli_data.py	0	this file contains deprecated code that can only be used with the old `model.fit`-style sentence transformers v2.x train
HIGH	…_transformers/sentence_transformer/readers/sts_data.py	0	this file contains deprecated code that can only be used with the old `model.fit`-style sentence transformers v2.x train
HIGH	…nsformers/sentence_transformer/readers/paired_files.py	0	this file contains deprecated code that can only be used with the old `model.fit`-style sentence transformers v2.x train
HIGH	…sformers/sentence_transformer/readers/input_example.py	0	this file contains deprecated code that can only be used with the old `model.fit`-style sentence transformers v2.x train
HIGH	…formers/sentence_transformer/readers/label_sentence.py	0	this file contains deprecated code that can only be used with the old `model.fit`-style sentence transformers v2.x train
HIGH	…e_transformers/sentence_transformer/readers/triplet.py	0	this file contains deprecated code that can only be used with the old `model.fit`-style sentence transformers v2.x train
HIGH	sentence_transformers/cross_encoder/losses/rank_net.py	0	get configuration parameters for this loss function. returns: dictionary containing the configuration parameters
HIGH	sentence_transformers/cross_encoder/losses/list_net.py	0	get configuration parameters for this loss function. returns: dictionary containing the configuration parameters
HIGH	sentence_transformers/cross_encoder/losses/plist_mle.py	0	get configuration parameters for this loss function. returns: dictionary containing the configuration parameters
HIGH	sentence_transformers/cross_encoder/losses/list_mle.py	0	get configuration parameters for this loss function. returns: dictionary containing the configuration parameters
HIGH	…tence_transformers/cross_encoder/losses/lambda_loss.py	0	get configuration parameters for this loss function. returns: dictionary containing the configuration parameters
HIGH	…ce_transformers/cross_encoder/evaluation/deprecated.py	0	this evaluator has been deprecated in favor of the more general crossencoderclassificationevaluator.
HIGH	…ce_transformers/cross_encoder/evaluation/deprecated.py	0	this evaluator has been deprecated in favor of the more general crossencoderclassificationevaluator.
HIGH	…ce_transformers/cross_encoder/evaluation/deprecated.py	0	this evaluator has been deprecated in favor of the more general crossencoderclassificationevaluator.
HIGH	…ce_transformers/cross_encoder/evaluation/deprecated.py	0	this evaluator has been deprecated in favor of the more general crossencoderclassificationevaluator.
HIGH	sentence_transformers/sparse_encoder/losses/splade.py	0	get the configuration dictionary. returns: dictionary containing the configuration parameters
HIGH	sentence_transformers/sparse_encoder/losses/csr.py	0	get the configuration dictionary. returns: dictionary containing the configuration parameters
HIGH	sentence_transformers/sparse_encoder/losses/csr.py	0	get the configuration dictionary. returns: dictionary containing the configuration parameters
HIGH	tests/sentence_transformer/test_model_card.py	0	dummy dataset for testing purposes. the dataset looks as follows: { "anchor": ["anchor 1", "anchor 2", ..., "anchor 10"]
HIGH	tests/cross_encoder/test_model_card.py	0	dummy dataset for testing purposes. the dataset looks as follows: { "anchor": ["anchor 1", "anchor 2", ..., "anchor 10"]
HIGH	tests/sparse_encoder/test_model_card.py	0	dummy dataset for testing purposes. the dataset looks as follows: { "anchor": ["anchor 1", "anchor 2", ..., "anchor 10"]
HIGH	…ransformer/evaluation/test_label_accuracy_evaluator.py	0	tests the correct computation of evaluation scores from binaryclassificationevaluator
HIGH	…mer/evaluation/test_binary_classification_evaluator.py	0	tests the correct computation of evaluation scores from binaryclassificationevaluator
HIGH	…sformer/evaluation/test_paraphrase_mining_evaluator.py	0	tests the correct computation of evaluation scores from binaryclassificationevaluator
HIGH	tests/util/test_hard_negatives.py	0	return a sample dataset with multiple matching passages for each query.
HIGH	tests/util/test_hard_negatives.py	0	return a sample dataset with multiple matching passages for each query.
HIGH	tests/util/test_hard_negatives.py	0	return a sample dataset with multiple matching passages for each query.
HIGH	tests/cross_encoder/test_model.py	0	\ <\|im_start\|>system judge whether the document meets the requirements based on the query and the instruct provided. not
HIGH	tests/cross_encoder/test_model.py	0	\ <\|im_start\|>system judge whether the document meets the requirements based on the query and the instruct provided. not
HIGH	tests/cross_encoder/test_model.py	0	\ <\|im_start\|>system judge whether the document meets the requirements based on the query and the instruct provided. not
HIGH	tests/base/test_modality.py	0	malformed urls (e.g. containing unclosed brackets) should not crash.
HIGH	tests/base/test_modality.py	0	malformed urls (e.g. containing unclosed brackets) should not crash.
HIGH	tests/base/test_modality.py	0	malformed urls (e.g. containing unclosed brackets) should not crash.
HIGH	tests/base/modules/transformer/test_text_generation.py	0	create a transformer instance and return it with its supported modalities.
HIGH	tests/base/modules/transformer/test_fill_mask.py	0	create a transformer instance and return it with its supported modalities.
HIGH	tests/base/modules/transformer/test_any_to_any.py	0	create a transformer instance and return it with its supported modalities.
HIGH	…se/modules/transformer/test_sequence_classification.py	0	create a transformer instance and return it with its supported modalities.
HIGH	tests/base/modules/transformer/test_text_generation.py	0	test inference with each supported modality (single and multi-modal).
HIGH	…ts/base/modules/transformer/test_feature_extraction.py	0	test inference with each supported modality (single and multi-modal).
HIGH	tests/base/modules/transformer/test_any_to_any.py	0	test inference with each supported modality (single and multi-modal).
HIGH	…se/modules/transformer/test_sequence_classification.py	0	test inference with each supported modality (single and multi-modal).
HIGH	tests/base/modules/transformer/test_text_generation.py	0	test inference with pair inputs for each supported modality combination.
HIGH	tests/base/modules/transformer/test_any_to_any.py	0	test inference with pair inputs for each supported modality combination.
HIGH	…se/modules/transformer/test_sequence_classification.py	0	test inference with pair inputs for each supported modality combination.
HIGH	…former/unsupervised_learning/TSDAE/train_stsb_tsdae.py	0	applies noise by randomly deleting words. warning: nltk's tokenization/detokenization is designed primarily for english.
40 more matches not shown…

Self-Referential Comments96 hits · 291 pts

Severity	File	Line	Snippet
MEDIUM	sentence_transformers/sentence_transformer/model.py	856	# Create a pool if not provided, but a list of devices is
MEDIUM	…transformers/sentence_transformer/losses/gist_embed.py	193	# Define the anchor threshold
MEDIUM	…transformers/sentence_transformer/losses/gist_embed.py	211	# Create a mask to protect true positive pairs in the anchor-positive matrix (i.e., diagonal elements)
MEDIUM	…rmers/sentence_transformer/losses/cached_gist_embed.py	333	# Define the anchor threshold
MEDIUM	…rmers/sentence_transformer/losses/cached_gist_embed.py	351	# Create a mask to protect true positive pairs in the anchor-positive matrix (i.e., diagonal elements)
MEDIUM	…s/sentence_transformer/evaluation/paraphrase_mining.py	66	# Create a mapping from qid to question & a list of duplicates (qid1, qid2)
MEDIUM	sentence_transformers/util/tensor.py	160	# Create a mask of zeros, then set the top-k positions to 1
MEDIUM	sentence_transformers/util/tensor.py	165	# Create a sparse tensor with only the top values
MEDIUM	sentence_transformers/util/retrieval.py	163	"""This function is deprecated. Use semantic_search instead"""
MEDIUM	sentence_transformers/cross_encoder/model.py	297	# Create a pool if is not provided, but a list of devices is
MEDIUM	…ers/cross_encoder/losses/multiple_negatives_ranking.py	137	# Create a mask for each anchor to each candidate index, where the matching positive
MEDIUM	sentence_transformers/cross_encoder/losses/plist_mle.py	224	# Create a mask for valid entries
MEDIUM	…ransformers/cross_encoder/evaluation/classification.py	51	# Create a list of pairs, and map the labels to the labels that the model knows
MEDIUM	sentence_transformers/sparse_encoder/model.py	723	# Create a pool if not provided, but a list of devices is
MEDIUM	sentence_transformers/base/sampler.py	533	# Create a random numpy permutation using int32 (or int64 if necessary)
MEDIUM	sentence_transformers/base/modules/transformer.py	1940	# This method is only called if this model has a modules.json, i.e. it's already been saved
MEDIUM	sentence_transformers/base/modules/router.py	81	# Create an asymmetric model with different encoders for queries and documents
MEDIUM	tests/sentence_transformer/test_model.py	1201	# Create a simple dataset with a text column
MEDIUM	tests/sentence_transformer/test_model.py	1322	# Create a Router with mixed modules
MEDIUM	tests/sentence_transformer/test_model.py	986	# Create a mock model with required prompts
MEDIUM	tests/sentence_transformer/test_model.py	1043	# Create a mock model with required prompts
MEDIUM	tests/sentence_transformer/test_multi_process.py	89	# Create a pool
MEDIUM	tests/sentence_transformer/test_multi_process.py	163	# Create a pool
MEDIUM	tests/sentence_transformer/test_trainer.py	197	# Create a new model card if a Trainer was initialized
MEDIUM	tests/sentence_transformer/test_trainer.py	801	# Define a custom batch sampler function
MEDIUM	tests/sentence_transformer/test_trainer.py	931	# Define a custom multi-dataset batch sampler function
MEDIUM	tests/util/test_hard_negatives.py	985	# Create a larger dataset with 32 entries
MEDIUM	tests/util/test_hard_negatives.py	1100	# Create a dataset with just 2 pairs
MEDIUM	tests/cross_encoder/test_model.py	753	# Create a simple dataset with a text column
MEDIUM	tests/cross_encoder/test_trainer.py	101	# Create a new model card if a Trainer was initialized
MEDIUM	tests/sparse_encoder/test_model.py	426	# Create a simple dataset with a text column
MEDIUM	tests/sparse_encoder/test_model.py	136	# Create an empty sparse tensor
MEDIUM	tests/sparse_encoder/test_model.py	171	# Create a batch where the first sample has values but the second is all zeros
MEDIUM	tests/sparse_encoder/test_multi_process.py	62	# Create a pool
MEDIUM	tests/sparse_encoder/modules/test_csr.py	11	# Create a wrapper to measure outputs of the forward method
MEDIUM	tests/sparse_encoder/modules/test_csr.py	61	# Create the wrapper and replace the forward method
MEDIUM	tests/base/samplers/test_no_duplicates_batch_sampler.py	39	# Create a list of two 0's, two 1's, two 2's, ... two 49's. Then shuffle.
MEDIUM	tests/base/modules/test_router.py	683	# Create a Router with different module configurations for each route
MEDIUM	tests/base/modules/test_router.py	693	# Create a SentenceTransformer with static_embedding followed by router
MEDIUM	tests/base/modules/test_router.py	67	# Create a custom ModuleDict subclass to track access
MEDIUM	tests/base/modules/test_router.py	209	# Create a Router with StaticEmbedding modules
MEDIUM	tests/base/modules/test_router.py	313	# Create a Router with StaticEmbedding modules
MEDIUM	tests/base/modules/test_router.py	439	# Create a Router with StaticEmbedding modules
MEDIUM	tests/base/modules/test_router.py	457	# Create a loss function that works with router
MEDIUM	tests/base/modules/test_router.py	481	# Create a Router with StaticEmbedding modules
MEDIUM	tests/base/modules/test_router.py	493	# Create a loss function that works with router
MEDIUM	tests/base/modules/test_router.py	1356	# Create an object that will fail modality inference
MEDIUM	tests/base/modules/test_dense.py	92	# Create a Dense layer with custom keys
MEDIUM	…/training/data_augmentation/train_sts_indomain_bm25.py	218	# Define the training arguments
MEDIUM	…/training/data_augmentation/train_sts_indomain_bm25.py	239	# Create the trainer & start training
MEDIUM	…raining/data_augmentation/train_sts_indomain_nlpaug.py	137	# Define the training arguments
MEDIUM	…raining/data_augmentation/train_sts_indomain_nlpaug.py	158	# Create the trainer & start training
MEDIUM	…transformer/training/other/training_batch_hard_trec.py	45	# Create a dev set from train set
MEDIUM	…ansformer/training/other/training_gooaq_infonce_gor.py	42	# Define a custom loss that combines InfoNCE and Global Orthogonal Regularization
MEDIUM	…ransformer/training/distillation/model_distillation.py	111	# Create a relatively small dataset for evaluation
MEDIUM	…ransformer/training/distillation/model_distillation.py	116	# Create an STSB evaluator
MEDIUM	…ransformer/training/distillation/model_distillation.py	165	# Define the training arguments
MEDIUM	…ransformer/training/distillation/model_distillation.py	189	# Create the trainer & start training
MEDIUM	…ing/distillation/model_distillation_layer_reduction.py	58	# Create a smaller student model by using only some of the teacher layers
MEDIUM	…ing/distillation/model_distillation_layer_reduction.py	134	# Create a relatively small dataset for evaluation
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Excessive Try-Catch Wrapping174 hits · 176 pts

Severity	File	Line	Snippet
LOW	…entence_transformer/deprecated_model_card_templates.py	189	except Exception as e:
MEDIUM	…entence_transformer/deprecated_model_card_templates.py	160	def get_train_objective_info(dataloader, loss):
LOW	…nsformers/sentence_transformer/evaluation/nano_beir.py	477	except Exception as e:
LOW	sentence_transformers/util/hard_negatives.py	457	except Exception:
LOW	sentence_transformers/util/logging.py	19	except Exception:
MEDIUM	sentence_transformers/util/logging.py	12	def emit(self, record) -> None:
LOW	sentence_transformers/util/misc.py	69	except Exception:
LOW	sentence_transformers/util/file_io.py	192	except Exception as first_error:
LOW	sentence_transformers/util/file_io.py	249	except Exception:
LOW	sentence_transformers/cross_encoder/model.py	383	except Exception as e:
LOW	sentence_transformers/cross_encoder/model.py	387	except Exception:
LOW	…nce_transformers/cross_encoder/evaluation/nano_beir.py	398	except Exception as e:
LOW	sentence_transformers/sparse_encoder/model.py	788	except Exception as e:
LOW	sentence_transformers/sparse_encoder/model.py	792	except Exception:
LOW	sentence_transformers/base/model.py	754	except Exception:
LOW	sentence_transformers/base/model.py	920	except Exception as exc:
LOW	sentence_transformers/base/model.py	1093	except Exception as exc:
LOW	sentence_transformers/base/model.py	1103	except Exception:
LOW	sentence_transformers/base/trainer.py	685	except Exception:
LOW	sentence_transformers/base/trainer.py	690	except Exception as exc:
MEDIUM	sentence_transformers/base/model_card.py	1424	def try_to_float(metric_value):
LOW	sentence_transformers/base/model_card.py	1937	except Exception as exc:
LOW	sentence_transformers/base/model_card.py	1945	except Exception as exc:
LOW	sentence_transformers/base/model_card.py	1953	except Exception as exc:
LOW	sentence_transformers/base/model_card.py	1960	except Exception as exc:
LOW	sentence_transformers/base/model_card.py	456	except Exception:
LOW	sentence_transformers/base/model_card.py	851	except Exception:
LOW	sentence_transformers/base/model_card.py	894	except Exception:
LOW	sentence_transformers/base/model_card.py	1318	except Exception:
LOW	sentence_transformers/base/model_card.py	1387	except Exception:
LOW	sentence_transformers/base/model_card.py	1427	except Exception:
LOW	sentence_transformers/base/model_card.py	1557	except Exception:
LOW	sentence_transformers/base/model_card.py	1565	except Exception:
LOW	sentence_transformers/base/model_card.py	1587	except Exception:
LOW	sentence_transformers/base/model_card.py	1842	except Exception:
LOW	sentence_transformers/base/model_card.py	1894	except Exception:
LOW	sentence_transformers/base/model_card.py	1905	except Exception as exc:
LOW	sentence_transformers/base/model_card.py	1911	except Exception as exc:
LOW	sentence_transformers/base/model_card.py	1922	except Exception as exc:
LOW	sentence_transformers/base/model_card.py	495	except Exception:
LOW	sentence_transformers/base/modules/transformer.py	1735	except Exception:
LOW	tests/cross_encoder/test_model_card.py	290	except Exception:
LOW	tests/sparse_encoder/test_pretrained.py	142	except Exception as e:
LOW	tests/sparse_encoder/test_pretrained.py	153	except Exception as e:
LOW	tests/sparse_encoder/test_pretrained.py	183	except Exception as e:
LOW	tests/sparse_encoder/test_trainer.py	127	except Exception as e:
LOW	tests/base/test_model_card.py	281	except Exception:
LOW	tests/base/test_modality.py	694	except Exception as exc:
LOW	tests/base/modules/transformer/test_text_generation.py	86	except Exception as e:
LOW	tests/base/modules/transformer/conftest.py	193	except Exception as e:
LOW	tests/base/modules/transformer/conftest.py	686	except Exception:
LOW	tests/base/modules/transformer/test_fill_mask.py	78	except Exception as e:
LOW	…ts/base/modules/transformer/test_feature_extraction.py	96	except Exception as e:
LOW	tests/base/modules/transformer/test_any_to_any.py	106	except Exception as e:
LOW	…se/modules/transformer/test_sequence_classification.py	87	except Exception as e:
LOW	docs/cross_encoder/training_overview.md	865	except Exception:
LOW	docs/cross_encoder/training_overview.md	1069	except Exception:
LOW	…ples/sentence_transformer/training/nli/training_nli.py	117	except Exception:
LOW	…s/sentence_transformer/training/nli/training_nli_v2.py	126	except Exception:
LOW	…entence_transformer/training/nli/training_nli_angle.py	127	except Exception:
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Docstring Block Structure18 hits · 90 pts

Severity	File	Line	Snippet
HIGH	sentence_transformers/sentence_transformer/trainer.py	37	SentenceTransformerTrainer is a simple but feature-complete training and eval loop for PyTorch based on the 🤗 T
HIGH	…rmers/sentence_transformer/modules/static_embedding.py	182	Creates a StaticEmbedding instance from a distillation process using the `model2vec` package. Args:
HIGH	…rmers/sentence_transformer/modules/static_embedding.py	245	Create a StaticEmbedding instance from a model2vec model. This method loads a pre-trained model2vec model
HIGH	sentence_transformers/util/misc.py	41	Import a dotted module path and return the attribute/class designated by the last name in the path. Raise Impor
HIGH	sentence_transformers/util/similarity.py	264	Converts a similarity function name or enum value to the corresponding similarity function. Args:
HIGH	sentence_transformers/util/similarity.py	302	Converts a similarity function into a pairwise similarity function. The pairwise similarity function r
HIGH	sentence_transformers/util/quantization.py	31	Performs semantic search using the FAISS library. Rescoring will be performed if: 1. `rescore` is True
HIGH	sentence_transformers/util/quantization.py	198	Performs semantic search using the usearch library. Rescoring will be performed if: 1. `rescore` is True
HIGH	sentence_transformers/util/file_io.py	41	Checks if the given model name or path corresponds to a SentenceTransformer model. Args: model_name_or
HIGH	sentence_transformers/util/file_io.py	82	Loads a file from a local or remote location. Args: model_name_or_path (str): The model name or path.
HIGH	sentence_transformers/util/file_io.py	141	Loads the subfolder path for a given model name or path. Args: model_name_or_path (str): The name or p
HIGH	sentence_transformers/util/file_io.py	206	Download a URL to a local file with a progress bar. The content is streamed in chunks and first written to a tempor
HIGH	sentence_transformers/backend/optimize.py	27	Export an optimized ONNX model from a SentenceTransformer, SparseEncoder, or CrossEncoder model. The O1-O4 opt
HIGH	sentence_transformers/backend/quantize.py	32	Export a quantized ONNX model from a SentenceTransformer, SparseEncoder, or CrossEncoder model. This function
HIGH	sentence_transformers/backend/quantize.py	119	Export a quantized OpenVINO model from a SentenceTransformer, SparseEncoder, or CrossEncoder model. This funct
HIGH	sentence_transformers/cross_encoder/model.py	556	Performs predictions with the CrossEncoder on the given input pairs. .. tip:: Adjusting `
HIGH	sentence_transformers/base/modality.py	550	Infer the modality of a single input sample by inspecting its type/structure. Pure type-based detection, does not r
HIGH	sentence_transformers/base/modules/module.py	311	A utility function to load the PyTorch weights of a model from a checkpoint. The checkpoint can be either a

Deep Nesting91 hits · 84 pts

Severity	File	Line
LOW	sentence_transformers/sentence_transformer/model.py	481
LOW	sentence_transformers/sentence_transformer/model.py	838
LOW	sentence_transformers/sentence_transformer/model.py	903
LOW	sentence_transformers/sentence_transformer/fit_mixin.py	63
LOW	sentence_transformers/sentence_transformer/fit_mixin.py	407
LOW	sentence_transformers/sentence_transformer/fit_mixin.py	465
LOW	…tence_transformer/losses/multiple_negatives_ranking.py	235
LOW	…ransformer/losses/cached_multiple_negatives_ranking.py	65
LOW	…ransformer/losses/cached_multiple_negatives_ranking.py	153
LOW	…ransformer/losses/cached_multiple_negatives_ranking.py	425
LOW	…transformers/sentence_transformer/losses/matryoshka.py	92
LOW	…rmers/sentence_transformer/losses/cached_gist_embed.py	46
LOW	…tence_transformer/datasets/no_duplicates_dataloader.py	29
LOW	…ntence_transformer/evaluation/information_retrieval.py	299
LOW	…ntence_transformer/evaluation/information_retrieval.py	447
LOW	…formers/sentence_transformer/evaluation/translation.py	102
LOW	…s/sentence_transformer/evaluation/paraphrase_mining.py	245
LOW	…e_transformers/sentence_transformer/modules/pooling.py	163
LOW	…e_transformers/sentence_transformer/modules/pooling.py	237
LOW	…rmers/sentence_transformer/modules/tokenizer/phrase.py	63
LOW	sentence_transformers/util/hard_negatives.py	25
LOW	sentence_transformers/util/deprecated_import.py	210
LOW	sentence_transformers/util/quantization.py	18
LOW	sentence_transformers/util/quantization.py	185
LOW	sentence_transformers/util/quantization.py	371
LOW	sentence_transformers/util/retrieval.py	89
LOW	sentence_transformers/util/retrieval.py	167
LOW	sentence_transformers/util/retrieval.py	258
LOW	sentence_transformers/util/environment.py	40
LOW	sentence_transformers/util/file_io.py	205
LOW	sentence_transformers/util/decorators.py	92
LOW	sentence_transformers/util/decorators.py	115
LOW	sentence_transformers/backend/utils.py	155
LOW	sentence_transformers/cross_encoder/model.py	279
LOW	sentence_transformers/cross_encoder/model.py	353
LOW	sentence_transformers/cross_encoder/fit_mixin.py	61
LOW	sentence_transformers/cross_encoder/fit_mixin.py	417
LOW	sentence_transformers/sparse_encoder/model.py	706
LOW	…rs/sparse_encoder/evaluation/reciprocal_rank_fusion.py	105
LOW	…_transformers/sparse_encoder/modules/splade_pooling.py	65
LOW	sentence_transformers/base/model.py	830
LOW	sentence_transformers/base/model.py	1028
LOW	sentence_transformers/base/modality.py	231
LOW	sentence_transformers/base/modality.py	440
LOW	sentence_transformers/base/modality.py	464
LOW	sentence_transformers/base/data_collator.py	114
LOW	sentence_transformers/base/trainer.py	392
LOW	sentence_transformers/base/trainer.py	417
LOW	sentence_transformers/base/trainer.py	532
LOW	sentence_transformers/base/trainer.py	815
LOW	sentence_transformers/base/trainer.py	1206
LOW	sentence_transformers/base/model_card.py	429
LOW	sentence_transformers/base/model_card.py	512
LOW	sentence_transformers/base/model_card.py	594
LOW	sentence_transformers/base/model_card.py	696
LOW	sentence_transformers/base/model_card.py	792
LOW	sentence_transformers/base/model_card.py	1361
LOW	sentence_transformers/base/model_card.py	1889
LOW	sentence_transformers/base/modules/transformer.py	452
LOW	sentence_transformers/base/modules/transformer.py	581
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Redundant / Tautological Comments48 hits · 64 pts

Severity	File	Line	Snippet
LOW	…mers/sentence_transformer/losses/batch_hard_triplet.py	240	# Check if labels[i] == labels[j]
LOW	…mers/sentence_transformer/losses/batch_hard_triplet.py	254	# Check if labels[i] != labels[k]
LOW	sentence_transformers/util/tensor.py	23	# Check if list contains sparse tensors
LOW	sentence_transformers/util/retrieval.py	331	# Check if we need to increase sort_max_size
LOW	sentence_transformers/cross_encoder/model_card.py	211	# Check if any pair element is non-text (from usage_examples before asset saving)
LOW	…arse_encoder/evaluation/sparse_embedding_similarity.py	78	# Print the results
LOW	…rse_encoder/evaluation/sparse_information_retrieval.py	128	# Print the results
LOW	…ansformers/sparse_encoder/evaluation/sparse_triplet.py	90	# Print the results
LOW	…sformers/sparse_encoder/evaluation/sparse_nano_beir.py	171	# Print the results
LOW	…rse_encoder/evaluation/sparse_binary_classification.py	104	# Print the results
LOW	…e_transformers/sparse_encoder/evaluation/sparse_mse.py	78	# Print the results
LOW	…ormers/sparse_encoder/evaluation/sparse_translation.py	75	# Print the results
LOW	…sformers/sparse_encoder/evaluation/sparse_reranking.py	102	# Print the results
LOW	…mers/sparse_encoder/modules/sparse_static_embedding.py	202	# Check if we have a JSON path in config
LOW	sentence_transformers/base/model.py	971	# Check if this is a Sentence Transformer model
LOW	sentence_transformers/base/model.py	1057	# Check if the config_sentence_transformers.json file exists (exists since v2 of the framework)
LOW	sentence_transformers/base/model.py	1082	# Check if a readme exists. README is optional metadata; a transient Hub error
LOW	sentence_transformers/base/model.py	1136	# Check if the `load` method only accepts a single parameter (the path to the local directory).
LOW	sentence_transformers/base/model_card.py	651	# Check if the model has a tuple modality whose parts all match available columns.
LOW	tests/sparse_encoder/utils.py	26	# Check if shape matches
LOW	tests/sparse_encoder/utils.py	40	# Check if indices are the same
LOW	tests/sparse_encoder/utils.py	44	# Check if values are close
LOW	tests/sparse_encoder/test_trainer.py	116	# Check if model parameters have changed after training
LOW	…sparse_encoder/modules/test_sparse_static_embedding.py	55	# Check if embeddings are the same before and after save/load
LOW	…sparse_encoder/modules/test_sparse_static_embedding.py	58	# Check if SparseStaticEmbedding weights are maintained after loading
LOW	…modules/transformer/update_transformers_tiny_models.py	42	# Check if the model_id contains the architecture name
LOW	…raining/data_augmentation/train_sts_qqp_crossdomain.py	58	# Check if the QQP dataset exists. If not, download and extract
LOW	…er/training/quora_duplicate_questions/create_splits.py	510	####### Write files for Information Retrieval #####
LOW	…/embedding-quantization/semantic_search_recommended.py	120	# Output the results
LOW	…transformer/applications/clustering/fast_clustering.py	32	# Check if the dataset exists. If not, download and extract
LOW	…tions/semantic-search/semantic_search_quora_pytorch.py	35	# Check if embedding cache path exists
LOW	…tions/semantic-search/semantic_search_quora_pytorch.py	37	# Check if the dataset exists. If not, download and extract
LOW	…cations/semantic-search/semantic_search_quora_annoy.py	57	# Check if embedding cache path exists
LOW	…cations/semantic-search/semantic_search_quora_annoy.py	59	# Check if the dataset exists. If not, download and extract
LOW	…tions/semantic-search/semantic_search_quora_hnswlib.py	47	# Check if embedding cache path exists
LOW	…tions/semantic-search/semantic_search_quora_hnswlib.py	49	# Check if the dataset exists. If not, download and extract
LOW	…cations/semantic-search/semantic_search_quora_faiss.py	61	# Check if embedding cache path exists
LOW	…cations/semantic-search/semantic_search_quora_faiss.py	63	# Check if the dataset exists. If not, download and extract
LOW	…/cross_encoder/applications/cross_encoder_reranking.py	41	# Check if embedding cache path exists
LOW	…parse_encoder/evaluation/sparse_reranking_evaluator.py	53	# Print the results
LOW	…coder/evaluation/sparse_nanobeir_advanced_evaluator.py	45	# Print the results
LOW	…arse_encoder/evaluation/sparse_similarity_evaluator.py	31	# Print the results
LOW	…rse_encoder/evaluation/sparse_translation_evaluator.py	30	# Print the results
LOW	…/sparse_encoder/evaluation/sparse_triplet_evaluator.py	37	# Print the results
LOW	…parse_encoder/evaluation/sparse_retrieval_evaluator.py	69	# Print the results
LOW	…sparse_encoder/evaluation/sparse_nanobeir_evaluator.py	94	# Print the results
LOW	…_encoder/evaluation/sparse_classification_evaluator.py	58	# Print the results
LOW	…ples/sparse_encoder/evaluation/sparse_mse_evaluator.py	32	# Print the results

AI Slop Vocabulary7 hits · 14 pts

Severity	File	Line	Snippet
LOW	…transformers/sentence_transformer/losses/gist_embed.py	240	# so the label for anchor[i] is i. This means that we can just use arange
LOW	…rmers/sentence_transformer/losses/cached_gist_embed.py	316	# so the label for anchor[i] is i. This means that we can just use arange
LOW	sentence_transformers/base/trainer.py	514	# if loss is nan or inf simply add the average of previous logged losses
LOW	sentence_transformers/base/trainer.py	567	# would not accept it. If None, we just call the super().log() method without it so that it works with all versi
LOW	sentence_transformers/base/trainer.py	644	# If the evaluator is not defined, we can just return the output
MEDIUM	…applications/parallel-sentence-mining/bitext_mining.py	27	# Model we want to use for bitext mining. sentence-transformers/LaBSE achieves state-of-the-art performance
MEDIUM	…rmer/applications/parallel-sentence-mining/bucc2018.py	25	# Model we want to use for bitext mining. sentence-transformers/LaBSE achieves state-of-the-art performance

Verbosity Indicators9 hits · 14 pts

Severity	File	Line	Snippet
LOW	…raining/data_augmentation/train_sts_qqp_crossdomain.py	107	# Step 1: Train cross-encoder model with STSbenchmark
LOW	…raining/data_augmentation/train_sts_qqp_crossdomain.py	152	# Step 2: Label QQP train dataset using cross-encoder (BERT) model
LOW	…raining/data_augmentation/train_sts_qqp_crossdomain.py	177	# Step 3: Train bi-encoder (SBERT) model with QQP dataset - Augmented SBERT
LOW	…/training/data_augmentation/train_sts_indomain_bm25.py	89	# Step 1: Train cross-encoder model with (gold) STS benchmark dataset
LOW	…/training/data_augmentation/train_sts_indomain_bm25.py	132	# Step 2: Label BM25 sampled STSb (silver dataset) using cross-encoder model
LOW	…/training/data_augmentation/train_sts_indomain_bm25.py	190	# Step 3: Train bi-encoder model with both (gold + silver) STSbenchmark dataset - Augmented SBERT
LOW	…ining/data_augmentation/train_sts_indomain_semantic.py	97	# Step 1: Train cross-encoder model with STSbenchmark
LOW	…ining/data_augmentation/train_sts_indomain_semantic.py	141	# Step 2: Find silver pairs to label
LOW	…ining/data_augmentation/train_sts_indomain_semantic.py	205	# Step 3: Train bi-encoder model with both STSbenchmark and labeled AllNlI - Augmented SBERT

Over-Commented Block11 hits · 11 pts

Severity	File	Line	Snippet
LOW	docs/conf.py	1	# Configuration file for the Sphinx documentation builder.
LOW	docs/sparse_encoder/training_overview.md	141	router = Router.for_query_document(
LOW	…ransformer/training/distillation/model_quantization.py	61	},
LOW	…transformer/training/multilingual/make_multilingual.py	81	# If we want, we can limit the maximum sequence length for the model
LOW	…ations/embedding-quantization/semantic_search_faiss.py	61	# In the first call we'll provide the `corpus_embeddings` and get the `corpus_index` back, which
LOW	…ions/embedding-quantization/semantic_search_usearch.py	61	# In the first call we'll provide the `corpus_embeddings` and get the `corpus_index` back, which
LOW	…ncoder/training/ms_marco/training_ms_marco_plistmle.py	101	# lambda_weight = PListMLELambdaWeight(rank_discount_fn=custom_discount)
LOW	examples/cross_encoder/training/distillation/README.md	61	# {"corpus_id": 4, "score": 0.91639173},
LOW	.github/workflows/sync-skills.yml	1	name: Sync skill to huggingface/skills
LOW	…train_sentence_transformer_static_embedding_example.py	1	#!/usr/bin/env python3
LOW	…cripts/train_sentence_transformer_with_lora_example.py	1	#!/usr/bin/env python3

Slop Phrases2 hits · 6 pts

Severity	File	Line	Snippet
MEDIUM	…te_questions/application_duplicate_questions_mining.py	10	# For demonstration purposes, we limit it to a few questions which all have on duplicate
MEDIUM	…ce_transformer/training/prompts/training_nq_prompts.py	26	# Feel free to adjust these variables:

Score History

Severity Breakdown

Pattern Findings