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SentenceTransformers Documentation — Sentence Transformers documentation
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| Texte d'ancre | Type | Juice |
|---|---|---|
| Installation | Interne | Passing Juice |
| Install with pip | Interne | Passing Juice |
| Install with Conda | Interne | Passing Juice |
| Install from Source | Interne | Passing Juice |
| Editable Install | Interne | Passing Juice |
| Install PyTorch with CUDA support | Interne | Passing Juice |
| Quickstart | Interne | Passing Juice |
| Sentence Transformer | Interne | Passing Juice |
| Cross Encoder | Interne | Passing Juice |
| Sparse Encoder | Interne | Passing Juice |
| Next Steps | Interne | Passing Juice |
| Migration Guide | Interne | Passing Juice |
| Migrating from v4.x to v5.x | Interne | Passing Juice |
| Migration for model.encode | Interne | Passing Juice |
| Migration for Asym to Router | Interne | Passing Juice |
| Migration of advanced usage | Interne | Passing Juice |
| Migrating from v3.x to v4.x | Interne | Passing Juice |
| Migration for CrossEncoder evaluators | Interne | Passing Juice |
| Migrating from v2.x to v3.x | Interne | Passing Juice |
| Usage | Interne | Passing Juice |
| Computing Embeddings | Interne | Passing Juice |
| Initializing a Sentence Transformer Model | Interne | Passing Juice |
| Calculating Embeddings | Interne | Passing Juice |
| Prompt Templates | Interne | Passing Juice |
| Input Sequence Length | Interne | Passing Juice |
| Multi-Process / Multi-GPU Encoding | Interne | Passing Juice |
| Semantic Textual Similarity | Interne | Passing Juice |
| Similarity Calculation | Interne | Passing Juice |
| Semantic Search | Interne | Passing Juice |
| Background | Interne | Passing Juice |
| Symmetric vs. Asymmetric Semantic Search | Interne | Passing Juice |
| Manual Implementation | Interne | Passing Juice |
| Optimized Implementation | Interne | Passing Juice |
| Speed Optimization | Interne | Passing Juice |
| Elasticsearch | Interne | Passing Juice |
| OpenSearch | Interne | Passing Juice |
| Approximate Nearest Neighbor | Interne | Passing Juice |
| Retrieve & Re-Rank | Interne | Passing Juice |
| Examples | Interne | Passing Juice |
| Retrieve & Re-Rank | Interne | Passing Juice |
| Retrieve & Re-Rank Pipeline | Interne | Passing Juice |
| Retrieval: Bi-Encoder | Interne | Passing Juice |
| Re-Ranker: Cross-Encoder | Interne | Passing Juice |
| Example Scripts | Interne | Passing Juice |
| Pre-trained Bi-Encoders (Retrieval) | Interne | Passing Juice |
| Pre-trained Cross-Encoders (Re-Ranker) | Interne | Passing Juice |
| Clustering | Interne | Passing Juice |
| k-Means | Interne | Passing Juice |
| Agglomerative Clustering | Interne | Passing Juice |
| Fast Clustering | Interne | Passing Juice |
| Topic Modeling | Interne | Passing Juice |
| Paraphrase Mining | Interne | Passing Juice |
| Translated Sentence Mining | Interne | Passing Juice |
| Margin Based Mining | Interne | Passing Juice |
| Examples | Interne | Passing Juice |
| Image Search | Interne | Passing Juice |
| Installation | Interne | Passing Juice |
| Usage | Interne | Passing Juice |
| Examples | Interne | Passing Juice |
| Embedding Quantization | Interne | Passing Juice |
| Binary Quantization | Interne | Passing Juice |
| Scalar (int8) Quantization | Interne | Passing Juice |
| Additional extensions | Interne | Passing Juice |
| Demo | Interne | Passing Juice |
| Try it yourself | Interne | Passing Juice |
| Creating Custom Models | Interne | Passing Juice |
| Structure of Sentence Transformer Models | Interne | Passing Juice |
| Sentence Transformer Model from a Transformers Model | Interne | Passing Juice |
| Advanced: Custom Modules | Interne | Passing Juice |
| Evaluation with MTEB | Interne | Passing Juice |
| Installation | Interne | Passing Juice |
| Evaluation | Interne | Passing Juice |
| Additional Arguments | Interne | Passing Juice |
| Results Handling | Interne | Passing Juice |
| Leaderboard Submission | Interne | Passing Juice |
| Speeding up Inference | Interne | Passing Juice |
| PyTorch | Interne | Passing Juice |
| ONNX | Interne | Passing Juice |
| OpenVINO | Interne | Passing Juice |
| Benchmarks | Interne | Passing Juice |
| Pretrained Models | Interne | Passing Juice |
| Original Models | Interne | Passing Juice |
| Semantic Search Models | Interne | Passing Juice |
| Multi-QA Models | Interne | Passing Juice |
| MSMARCO Passage Models | Interne | Passing Juice |
| Multilingual Models | Interne | Passing Juice |
| Semantic Similarity Models | Interne | Passing Juice |
| Bitext Mining | Interne | Passing Juice |
| Image & Text-Models | Interne | Passing Juice |
| INSTRUCTOR models | Interne | Passing Juice |
| Scientific Similarity Models | Interne | Passing Juice |
| Training Overview | Interne | Passing Juice |
| Why Finetune? | Interne | Passing Juice |
| Training Components | Interne | Passing Juice |
| Model | Interne | Passing Juice |
| Dataset | Interne | Passing Juice |
| Dataset Format | Interne | Passing Juice |
| Loss Function | Interne | Passing Juice |
| Training Arguments | Interne | Passing Juice |
| Evaluator | Interne | Passing Juice |
| Trainer | Interne | Passing Juice |
| Callbacks | Interne | Passing Juice |
| Multi-Dataset Training | Interne | Passing Juice |
| Deprecated Training | Interne | Passing Juice |
| Best Base Embedding Models | Interne | Passing Juice |
| Comparisons with CrossEncoder Training | Interne | Passing Juice |
| Dataset Overview | Interne | Passing Juice |
| Datasets on the Hugging Face Hub | Interne | Passing Juice |
| Pre-existing Datasets | Interne | Passing Juice |
| Loss Overview | Interne | Passing Juice |
| Loss Table | Interne | Passing Juice |
| Loss modifiers | Interne | Passing Juice |
| Distillation | Interne | Passing Juice |
| Commonly used Loss Functions | Interne | Passing Juice |
| Custom Loss Functions | Interne | Passing Juice |
| Training Examples | Interne | Passing Juice |
| Semantic Textual Similarity | Interne | Passing Juice |
| Training data | Interne | Passing Juice |
| Loss Function | Interne | Passing Juice |
| Natural Language Inference | Interne | Passing Juice |
| Data | Interne | Passing Juice |
| SoftmaxLoss | Interne | Passing Juice |
| MultipleNegativesRankingLoss | Interne | Passing Juice |
| Paraphrase Data | Interne | Passing Juice |
| Pre-Trained Models | Interne | Passing Juice |
| Quora Duplicate Questions | Interne | Passing Juice |
| Training | Interne | Passing Juice |
| MultipleNegativesRankingLoss | Interne | Passing Juice |
| Pretrained Models | Interne | Passing Juice |
| MS MARCO | Interne | Passing Juice |
| Bi-Encoder | Interne | Passing Juice |
| Matryoshka Embeddings | Interne | Passing Juice |
| Use Cases | Interne | Passing Juice |
| Results | Interne | Passing Juice |
| Training | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| Code Examples | Interne | Passing Juice |
| Adaptive Layers | Interne | Passing Juice |
| Use Cases | Interne | Passing Juice |
| Results | Interne | Passing Juice |
| Training | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| Code Examples | Interne | Passing Juice |
| Multilingual Models | Interne | Passing Juice |
| Extend your own models | Interne | Passing Juice |
| Training | Interne | Passing Juice |
| Datasets | Interne | Passing Juice |
| Sources for Training Data | Interne | Passing Juice |
| Evaluation | Interne | Passing Juice |
| Available Pre-trained Models | Interne | Passing Juice |
| Usage | Interne | Passing Juice |
| Performance | Interne | Passing Juice |
| Citation | Interne | Passing Juice |
| Model Distillation | Interne | Passing Juice |
| Knowledge Distillation | Interne | Passing Juice |
| Speed - Performance Trade-Off | Interne | Passing Juice |
| Dimensionality Reduction | Interne | Passing Juice |
| Quantization | Interne | Passing Juice |
| Augmented SBERT | Interne | Passing Juice |
| Motivation | Interne | Passing Juice |
| Extend to your own datasets | Interne | Passing Juice |
| Methodology | Interne | Passing Juice |
| Scenario 1: Limited or small annotated datasets (few labeled sentence-pairs) | Interne | Passing Juice |
| Scenario 2: No annotated datasets (Only unlabeled sentence-pairs) | Interne | Passing Juice |
| Training | Interne | Passing Juice |
| Citation | Interne | Passing Juice |
| Training with Prompts | Interne | Passing Juice |
| What are Prompts? | Interne | Passing Juice |
| Why would we train with Prompts? | Interne | Passing Juice |
| How do we train with Prompts? | Interne | Passing Juice |
| Training with PEFT Adapters | Interne | Passing Juice |
| Compatibility Methods | Interne | Passing Juice |
| Adding a New Adapter | Interne | Passing Juice |
| Loading a Pretrained Adapter | Interne | Passing Juice |
| Training Script | Interne | Passing Juice |
| Unsupervised Learning | Interne | Passing Juice |
| TSDAE | Interne | Passing Juice |
| SimCSE | Interne | Passing Juice |
| CT | Interne | Passing Juice |
| CT (In-Batch Negative Sampling) | Interne | Passing Juice |
| Masked Language Model (MLM) | Interne | Passing Juice |
| GenQ | Interne | Passing Juice |
| GPL | Interne | Passing Juice |
| Performance Comparison | Interne | Passing Juice |
| Domain Adaptation | Interne | Passing Juice |
| Domain Adaptation vs. Unsupervised Learning | Interne | Passing Juice |
| Adaptive Pre-Training | Interne | Passing Juice |
| GPL: Generative Pseudo-Labeling | Interne | Passing Juice |
| Hyperparameter Optimization | Interne | Passing Juice |
| HPO Components | Interne | Passing Juice |
| Putting It All Together | Interne | Passing Juice |
| Example Scripts | Interne | Passing Juice |
| Distributed Training | Interne | Passing Juice |
| Comparison | Interne | Passing Juice |
| FSDP | Interne | Passing Juice |
| Usage | Interne | Passing Juice |
| Cross-Encoder vs Bi-Encoder | Interne | Passing Juice |
| Cross-Encoder vs. Bi-Encoder | Interne | Passing Juice |
| When to use Cross- / Bi-Encoders? | Interne | Passing Juice |
| Cross-Encoders Usage | Interne | Passing Juice |
| Combining Bi- and Cross-Encoders | Interne | Passing Juice |
| Training Cross-Encoders | Interne | Passing Juice |
| Speeding up Inference | Interne | Passing Juice |
| PyTorch | Interne | Passing Juice |
| ONNX | Interne | Passing Juice |
| OpenVINO | Interne | Passing Juice |
| Benchmarks | Interne | Passing Juice |
| Pretrained Models | Interne | Passing Juice |
| MS MARCO | Interne | Passing Juice |
| SQuAD (QNLI) | Interne | Passing Juice |
| STSbenchmark | Interne | Passing Juice |
| Quora Duplicate Questions | Interne | Passing Juice |
| NLI | Interne | Passing Juice |
| Community Models | Interne | Passing Juice |
| Training Overview | Interne | Passing Juice |
| Why Finetune? | Interne | Passing Juice |
| Training Components | Interne | Passing Juice |
| Model | Interne | Passing Juice |
| Dataset | Interne | Passing Juice |
| Dataset Format | Interne | Passing Juice |
| Hard Negatives Mining | Interne | Passing Juice |
| Loss Function | Interne | Passing Juice |
| Training Arguments | Interne | Passing Juice |
| Evaluator | Interne | Passing Juice |
| Trainer | Interne | Passing Juice |
| Callbacks | Interne | Passing Juice |
| Multi-Dataset Training | Interne | Passing Juice |
| Training Tips | Interne | Passing Juice |
| Deprecated Training | Interne | Passing Juice |
| Comparisons with SentenceTransformer Training | Interne | Passing Juice |
| Loss Overview | Interne | Passing Juice |
| Loss Table | Interne | Passing Juice |
| Distillation | Interne | Passing Juice |
| Commonly used Loss Functions | Interne | Passing Juice |
| Custom Loss Functions | Interne | Passing Juice |
| Training Examples | Interne | Passing Juice |
| Semantic Textual Similarity | Interne | Passing Juice |
| Training data | Interne | Passing Juice |
| Loss Function | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| Natural Language Inference | Interne | Passing Juice |
| Data | Interne | Passing Juice |
| CrossEntropyLoss | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| Quora Duplicate Questions | Interne | Passing Juice |
| Training | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| MS MARCO | Interne | Passing Juice |
| Cross Encoder | Interne | Passing Juice |
| Training Scripts | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| Rerankers | Interne | Passing Juice |
| BinaryCrossEntropyLoss | Interne | Passing Juice |
| CachedMultipleNegativesRankingLoss | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| Model Distillation | Interne | Passing Juice |
| Cross Encoder Knowledge Distillation | Interne | Passing Juice |
| Inference | Interne | Passing Juice |
| Usage | Interne | Passing Juice |
| Computing Sparse Embeddings | Interne | Passing Juice |
| Initializing a Sparse Encoder Model | Interne | Passing Juice |
| Calculating Embeddings | Interne | Passing Juice |
| Input Sequence Length | Interne | Passing Juice |
| Controlling Sparsity | Interne | Passing Juice |
| Interpretability with SPLADE Models | Interne | Passing Juice |
| Multi-Process / Multi-GPU Encoding | Interne | Passing Juice |
| Semantic Textual Similarity | Interne | Passing Juice |
| Similarity Calculation | Interne | Passing Juice |
| Semantic Search | Interne | Passing Juice |
| Manual Search | Interne | Passing Juice |
| Vector Database Search | Interne | Passing Juice |
| Qdrant Integration | Interne | Passing Juice |
| OpenSearch Integration | Interne | Passing Juice |
| Elasticsearch Integration | Interne | Passing Juice |
| Seismic Integration | Interne | Passing Juice |
| SPLADE-index Integration | Interne | Passing Juice |
| Retrieve & Re-Rank | Interne | Passing Juice |
| Overview | Interne | Passing Juice |
| Interactive Demo: Simple Wikipedia Search | Interne | Passing Juice |
| Comprehensive Evaluation: Hybrid Search Pipeline | Interne | Passing Juice |
| Pre-trained Models | Interne | Passing Juice |
| Sparse Encoder Evaluation | Interne | Passing Juice |
| Example with Retrieval Evaluation: | Interne | Passing Juice |
| Speeding up Inference | Interne | Passing Juice |
| PyTorch | Interne | Passing Juice |
| ONNX | Interne | Passing Juice |
| OpenVINO | Interne | Passing Juice |
| Benchmarks | Interne | Passing Juice |
| Pretrained Models | Interne | Passing Juice |
| Core SPLADE Models | Interne | Passing Juice |
| Inference-Free SPLADE Models | Interne | Passing Juice |
| Model Collections | Interne | Passing Juice |
| Training Overview | Interne | Passing Juice |
| Why Finetune? | Interne | Passing Juice |
| Training Components | Interne | Passing Juice |
| Model | Interne | Passing Juice |
| Dataset | Interne | Passing Juice |
| Dataset Format | Interne | Passing Juice |
| Loss Function | Interne | Passing Juice |
| Training Arguments | Interne | Passing Juice |
| Evaluator | Interne | Passing Juice |
| Trainer | Interne | Passing Juice |
| Callbacks | Interne | Passing Juice |
| Multi-Dataset Training | Interne | Passing Juice |
| Training Tips | Interne | Passing Juice |
| Loss Overview | Interne | Passing Juice |
| Sparse specific Loss Functions | Interne | Passing Juice |
| SPLADE Loss | Interne | Passing Juice |
| CSR Loss | Interne | Passing Juice |
| Loss Table | Interne | Passing Juice |
| Distillation | Interne | Passing Juice |
| Commonly used Loss Functions | Interne | Passing Juice |
| Custom Loss Functions | Interne | Passing Juice |
| Training Examples | Interne | Passing Juice |
| Model Distillation | Interne | Passing Juice |
| MarginMSE | Interne | Passing Juice |
| MS MARCO | Interne | Passing Juice |
| SparseMultipleNegativesRankingLoss | Interne | Passing Juice |
| Semantic Textual Similarity | Interne | Passing Juice |
| Training data | Interne | Passing Juice |
| Loss Function | Interne | Passing Juice |
| Natural Language Inference | Interne | Passing Juice |
| Data | Interne | Passing Juice |
| SpladeLoss | Interne | Passing Juice |
| Quora Duplicate Questions | Interne | Passing Juice |
| Training | Interne | Passing Juice |
| Information Retrieval | Interne | Passing Juice |
| SparseMultipleNegativesRankingLoss (MNRL) | Interne | Passing Juice |
| Inference & Evaluation | Interne | Passing Juice |
| Sentence Transformer | Interne | Passing Juice |
| SentenceTransformer | Interne | Passing Juice |
| SentenceTransformer | Interne | Passing Juice |
| SentenceTransformerModelCardData | Interne | Passing Juice |
| SimilarityFunction | Interne | Passing Juice |
| Trainer | Interne | Passing Juice |
| SentenceTransformerTrainer | Interne | Passing Juice |
| Training Arguments | Interne | Passing Juice |
| SentenceTransformerTrainingArguments | Interne | Passing Juice |
| Losses | Interne | Passing Juice |
| BatchAllTripletLoss | Interne | Passing Juice |
| BatchHardSoftMarginTripletLoss | Interne | Passing Juice |
| BatchHardTripletLoss | Interne | Passing Juice |
| BatchSemiHardTripletLoss | Interne | Passing Juice |
| ContrastiveLoss | Interne | Passing Juice |
| OnlineContrastiveLoss | Interne | Passing Juice |
| ContrastiveTensionLoss | Interne | Passing Juice |
| ContrastiveTensionLossInBatchNegatives | Interne | Passing Juice |
| CoSENTLoss | Interne | Passing Juice |
| AnglELoss | Interne | Passing Juice |
| CosineSimilarityLoss | Interne | Passing Juice |
| DenoisingAutoEncoderLoss | Interne | Passing Juice |
| GISTEmbedLoss | Interne | Passing Juice |
| CachedGISTEmbedLoss | Interne | Passing Juice |
| MSELoss | Interne | Passing Juice |
| MarginMSELoss | Interne | Passing Juice |
| MatryoshkaLoss | Interne | Passing Juice |
| Matryoshka2dLoss | Interne | Passing Juice |
| AdaptiveLayerLoss | Interne | Passing Juice |
| MegaBatchMarginLoss | Interne | Passing Juice |
| MultipleNegativesRankingLoss | Interne | Passing Juice |
| CachedMultipleNegativesRankingLoss | Interne | Passing Juice |
| MultipleNegativesSymmetricRankingLoss | Interne | Passing Juice |
| CachedMultipleNegativesSymmetricRankingLoss | Interne | Passing Juice |
| SoftmaxLoss | Interne | Passing Juice |
| TripletLoss | Interne | Passing Juice |
| DistillKLDivLoss | Interne | Passing Juice |
| Samplers | Interne | Passing Juice |
| BatchSamplers | Interne | Passing Juice |
| MultiDatasetBatchSamplers | Interne | Passing Juice |
| Evaluation | Interne | Passing Juice |
| BinaryClassificationEvaluator | Interne | Passing Juice |
| EmbeddingSimilarityEvaluator | Interne | Passing Juice |
| InformationRetrievalEvaluator | Interne | Passing Juice |
| NanoBEIREvaluator | Interne | Passing Juice |
| MSEEvaluator | Interne | Passing Juice |
| ParaphraseMiningEvaluator | Interne | Passing Juice |
| RerankingEvaluator | Interne | Passing Juice |
| SentenceEvaluator | Interne | Passing Juice |
| SequentialEvaluator | Interne | Passing Juice |
| TranslationEvaluator | Interne | Passing Juice |
| TripletEvaluator | Interne | Passing Juice |
| Datasets | Interne | Passing Juice |
| ParallelSentencesDataset | Interne | Passing Juice |
| SentenceLabelDataset | Interne | Passing Juice |
| DenoisingAutoEncoderDataset | Interne | Passing Juice |
| NoDuplicatesDataLoader | Interne | Passing Juice |
| Modules | Interne | Passing Juice |
| Main Modules | Interne | Passing Juice |
| Further Modules | Interne | Passing Juice |
| Base Modules | Interne | Passing Juice |
| quantization | Interne | Passing Juice |
| Cross Encoder | Interne | Passing Juice |
| CrossEncoder | Interne | Passing Juice |
| CrossEncoder | Interne | Passing Juice |
| CrossEncoderModelCardData | Interne | Passing Juice |
| Trainer | Interne | Passing Juice |
| CrossEncoderTrainer | Interne | Passing Juice |
| Training Arguments | Interne | Passing Juice |
| CrossEncoderTrainingArguments | Interne | Passing Juice |
| Losses | Interne | Passing Juice |
| BinaryCrossEntropyLoss | Interne | Passing Juice |
| CrossEntropyLoss | Interne | Passing Juice |
| LambdaLoss | Interne | Passing Juice |
| ListMLELoss | Interne | Passing Juice |
| PListMLELoss | Interne | Passing Juice |
| ListNetLoss | Interne | Passing Juice |
| MultipleNegativesRankingLoss | Interne | Passing Juice |
| CachedMultipleNegativesRankingLoss | Interne | Passing Juice |
| MSELoss | Interne | Passing Juice |
| MarginMSELoss | Interne | Passing Juice |
| RankNetLoss | Interne | Passing Juice |
| Evaluation | Interne | Passing Juice |
| CrossEncoderRerankingEvaluator | Interne | Passing Juice |
| CrossEncoderNanoBEIREvaluator | Interne | Passing Juice |
| CrossEncoderClassificationEvaluator | Interne | Passing Juice |
| CrossEncoderCorrelationEvaluator | Interne | Passing Juice |
| Sparse Encoder | Interne | Passing Juice |
| SparseEncoder | Interne | Passing Juice |
| SparseEncoder | Interne | Passing Juice |
| SparseEncoderModelCardData | Interne | Passing Juice |
| SimilarityFunction | Interne | Passing Juice |
| Trainer | Interne | Passing Juice |
| SparseEncoderTrainer | Interne | Passing Juice |
| Training Arguments | Interne | Passing Juice |
| SparseEncoderTrainingArguments | Interne | Passing Juice |
| Losses | Interne | Passing Juice |
| SpladeLoss | Interne | Passing Juice |
| FlopsLoss | Interne | Passing Juice |
| CSRLoss | Interne | Passing Juice |
| CSRReconstructionLoss | Interne | Passing Juice |
| SparseMultipleNegativesRankingLoss | Interne | Passing Juice |
| SparseMarginMSELoss | Interne | Passing Juice |
| SparseDistillKLDivLoss | Interne | Passing Juice |
| SparseTripletLoss | Interne | Passing Juice |
| SparseCosineSimilarityLoss | Interne | Passing Juice |
| SparseCoSENTLoss | Interne | Passing Juice |
| SparseAnglELoss | Interne | Passing Juice |
| SparseMSELoss | Interne | Passing Juice |
| Evaluation | Interne | Passing Juice |
| SparseInformationRetrievalEvaluator | Interne | Passing Juice |
| SparseNanoBEIREvaluator | Interne | Passing Juice |
| SparseEmbeddingSimilarityEvaluator | Interne | Passing Juice |
| SparseBinaryClassificationEvaluator | Interne | Passing Juice |
| SparseTripletEvaluator | Interne | Passing Juice |
| SparseRerankingEvaluator | Interne | Passing Juice |
| SparseTranslationEvaluator | Interne | Passing Juice |
| SparseMSEEvaluator | Interne | Passing Juice |
| ReciprocalRankFusionEvaluator | Interne | Passing Juice |
| Modules | Interne | Passing Juice |
| SPLADE Pooling | Interne | Passing Juice |
| MLM Transformer | Interne | Passing Juice |
| SparseAutoEncoder | Interne | Passing Juice |
| SparseStaticEmbedding | Interne | Passing Juice |
| Callbacks | Interne | Passing Juice |
| SpladeRegularizerWeightSchedulerCallback | Interne | Passing Juice |
| Search Engines | Interne | Passing Juice |
| util | Interne | Passing Juice |
| Helper Functions | Interne | Passing Juice |
| Model Optimization | Interne | Passing Juice |
| Sentence Transformers | Interne | Passing Juice |
| Edit on GitHub | Externe | Passing Juice |
| v5.2 | Externe | Passing Juice |
| v5.2.1 | Externe | Passing Juice |
| v5.2.2 | Externe | Passing Juice |
| v5.2.3 | Externe | Passing Juice |
| UKP Lab | Externe | Passing Juice |
| 🤗 Hugging Face | Externe | Passing Juice |
| full announcement | Externe | Passing Juice |
| | Interne | Passing Juice |
| 10,000 pre-trained Sentence Transformers models | Externe | Passing Juice |
| Massive Text Embeddings Benchmark (MTEB) leaderboard | Externe | Passing Juice |
| Sentence Transformers repository | Externe | Passing Juice |
| | Interne | Passing Juice |
| | Interne | Passing Juice |
| | Interne | Passing Juice |
| Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks | Externe | Passing Juice |
| Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation | Externe | Passing Juice |
| data augmentation | Externe | Passing Juice |
| Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks | Externe | Passing Juice |
| Sphinx | Externe | Passing Juice |
| theme | Externe | Passing Juice |
| Read the Docs | Externe | Passing Juice |
Nuage de mots-clefs
Cohérence des mots-clefs
| Mot-clef | Contenu | Titre | Mots-clefs | Description | Niveaux de titre |
|---|
Url
Domaine : sbert.net
Longueur : 9
Favicon
Génial, votre site web dispose d'un favicon.
Imprimabilité
Aucun style CSS pour optimiser l'impression n'a pu être trouvé.
Langue
Bien. Votre langue est : en.
Dublin Core
Cette page ne profite pas des métadonnées Dublin Core.
Doctype
HTML 5
Encodage
Parfait. Votre charset est UTF-8.
Validité W3C
Erreurs : 0
Avertissements : 0
E-mail confidentialité
Génial, aucune adresse e-mail n'a été trouvé sous forme de texte!
HTML obsolètes
Génial! Nous n'avons pas trouvé de balises HTML obsolètes dans votre code.
Astuces vitesse
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Excellent, votre site n'utilise pas de tableaux imbriqués. |
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Parfait. Aucun style css inline n'a été trouvé dans vos tags HTML! |
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Mauvais, votre site web contient trop de fichiers CSS (plus de 4). |
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Mauvais, votre site web contient trop de fichiers javascript (plus de 6). |
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Parfait : votre site tire parti de gzip. |
Optimisation mobile
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Icône Apple |
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Méta tags viewport |
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Contenu FLASH |
Sitemap XML
Manquant
Votre site web ne dispose pas d’une sitemap XML, ce qui peut poser problème.
La sitemap recense les URLs que les moteurs de recherche peuvent indexer, tout en proposant d’éventuelles informations supplémentaires (comme la date de dernière mise à jour, la fréquence des changements, ainsi que leur niveau d’importance). Ceci permet aux moteurs de recherche de parcourir le site de façon plus efficace.
Robots.txt
https://sbert.net/robots.txt
Votre site dispose d’un fichier robots.txt, ce qui est optimal.
Mesures d'audience
Manquant
Nous n'avons trouvé aucun outil d'analytics sur ce site.
Un outil de mesure d'audience vous permet d'analyser l’activité des visiteurs sur votre site. Vous devriez installer au moins un outil Analytics. Il est souvent utile d’en rajouter un second, afin de confirmer les résultats du premier.
Free SEO Testing Tool est un outil gratuit de référencement qui vous aidera à analyser vos pages web