| --- |
| language: |
| - en |
| license: apache-2.0 |
| tags: |
| - sentence-transformers |
| - sparse-encoder |
| - sparse |
| - splade |
| base_model: distilbert/distilbert-base-uncased |
| pipeline_tag: feature-extraction |
| library_name: sentence-transformers |
| --- |
| |
| # SPLADE distilbert-base-uncased trained on python docstring code pairs |
|
|
| This is a [SPLADE Sparse Encoder](https://www.sbert.net/docs/sparse_encoder/usage/usage.html) model finetuned from [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) using the [sentence-transformers](https://www.SBERT.net) library. It maps sentences & paragraphs to a 30522-dimensional sparse vector space and can be used for semantic search and sparse retrieval. |
| ## Model Details |
|
|
| ### Model Description |
| - **Model Type:** SPLADE Sparse Encoder |
| - **Base model:** [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) <!-- at revision 12040accade4e8a0f71eabdb258fecc2e7e948be --> |
| - **Maximum Sequence Length:** 512 tokens |
| - **Output Dimensionality:** 30522 dimensions |
| - **Similarity Function:** Dot Product |
| <!-- - **Training Dataset:** Unknown --> |
| - **Language:** en |
| - **License:** apache-2.0 |
|
|
| ### Model Sources |
|
|
| - **Documentation:** [Sentence Transformers Documentation](https://sbert.net) |
| - **Documentation:** [Sparse Encoder Documentation](https://www.sbert.net/docs/sparse_encoder/usage/usage.html) |
| - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers) |
| - **Hugging Face:** [Sparse Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=sparse-encoder) |
|
|
| ### Full Model Architecture |
|
|
| ``` |
| SparseEncoder( |
| (0): MLMTransformer({'max_seq_length': 512, 'do_lower_case': False, 'architecture': 'DistilBertForMaskedLM'}) |
| (1): SpladePooling({'pooling_strategy': 'max', 'activation_function': 'relu', 'word_embedding_dimension': 30522}) |
| ) |
| ``` |
|
|
| ## Usage |
|
|
| ### Direct Usage (Sentence Transformers) |
|
|
| First install the Sentence Transformers library: |
|
|
| ```bash |
| pip install -U sentence-transformers |
| ``` |
|
|
| Then you can load this model and run inference. |
| ```python |
| from sentence_transformers import SparseEncoder |
| |
| # Download from the 🤗 Hub |
| model = SparseEncoder("pulkitmehtawork/sparse-distilbert-base-uncased-python-code-lightening") |
| # Run inference |
| sentences = [ |
| 'The weather is lovely today.', |
| "It's so sunny outside!", |
| 'He drove to the stadium.', |
| ] |
| embeddings = model.encode(sentences) |
| print(embeddings.shape) |
| # [3, 30522] |
| |
| # Get the similarity scores for the embeddings |
| similarities = model.similarity(embeddings, embeddings) |
| print(similarities) |
| # tensor([[2148.8340, 1376.2744, 850.4404], |
| # [1376.2744, 2056.9260, 898.0439], |
| # [ 850.4404, 898.0439, 2509.7507]]) |
| ``` |
|
|
| <!-- |
| ### Direct Usage (Transformers) |
|
|
| <details><summary>Click to see the direct usage in Transformers</summary> |
|
|
| </details> |
| --> |
|
|
| <!-- |
| ### Downstream Usage (Sentence Transformers) |
|
|
| You can finetune this model on your own dataset. |
|
|
| <details><summary>Click to expand</summary> |
|
|
| </details> |
| --> |
|
|
| <!-- |
| ### Out-of-Scope Use |
|
|
| *List how the model may foreseeably be misused and address what users ought not to do with the model.* |
| --> |
|
|
| <!-- |
| ## Bias, Risks and Limitations |
|
|
| *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.* |
| --> |
|
|
| <!-- |
| ### Recommendations |
|
|
| *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
| --> |
|
|
| ## Training Details |
|
|
| ### Framework Versions |
| - Python: 3.10.10 |
| - Sentence Transformers: 5.0.0 |
| - Transformers: 4.53.0 |
| - PyTorch: 2.7.0+cu128 |
| - Accelerate: 1.8.1 |
| - Datasets: 3.6.0 |
| - Tokenizers: 0.21.2 |
|
|
| ## Citation |
|
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| ### BibTeX |
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| <!-- |
| ## Glossary |
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| *Clearly define terms in order to be accessible across audiences.* |
| --> |
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| <!-- |
| ## Model Card Authors |
|
|
| *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.* |
| --> |
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| <!-- |
| ## Model Card Contact |
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| *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.* |
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