| --- |
| datasets: [] |
| language: [] |
| library_name: sentence-transformers |
| pipeline_tag: sentence-similarity |
| tags: |
| - sentence-transformers |
| - sentence-similarity |
| - feature-extraction |
| widget: [] |
| --- |
| |
| # SentenceTransformer |
|
|
| This is a finetuned version of [bge-m3](https://huggingface.co/BAAI/bge-m3) for the task of SQL table retrieval and ranking. |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/65cbd93c19683f98170c8d50/Y5GGGVC3RX0AUzA7oOmAe.png" width="800" height="800"> |
|
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| ## Model Details |
|
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| This model can be used to identify relevant SQL tables for query to SQL translation. |
|
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| The model was finetuned using a curated dataset of SQL table definitions and corresponding natural language queries. |
| The script used for finetuning: [Flag Embeddings](https://github.com/FlagOpen/FlagEmbedding/blob/master/examples/unified_finetune/unified_finetune_bge-m3_exmaple.sh) |
|
|
| ### Model Description |
| - **Model Type:** Sentence Transformer |
| <!-- - **Base model:** [Unknown](https://huggingface.co/unknown) --> |
| - **Maximum Sequence Length:** 8192 tokens |
| - **Output Dimensionality:** 1024 tokens |
| - **Similarity Function:** Cosine Similarity |
| <!-- - **Training Dataset:** Unknown --> |
| <!-- - **Language:** Unknown --> |
| <!-- - **License:** Unknown --> |
|
|
| ### Model Sources |
|
|
| - **Documentation:** [Sentence Transformers Documentation](https://sbert.net) |
| - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers) |
| - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) |
|
|
| ### Full Model Architecture |
|
|
| ``` |
| SentenceTransformer( |
| (0): Transformer({'max_seq_length': 8192, 'do_lower_case': False}) with Transformer model: XLMRobertaModel |
| (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) |
| (2): Normalize() |
| ) |
| ``` |
|
|
| ## Usage |
|
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| ### 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 SentenceTransformer |
| |
| # Download from the 🤗 Hub |
| model = SentenceTransformer("sentence_transformers_model_id") |
| # Run inference |
| sentences = [ |
| 'What is the total biomass of fish in farms with a water temperature above 25 degrees Celsius?', |
| 'CREATE TABLE Farm (FarmID INT, FarmName VARCHAR(50), WaterTemperature DECIMAL, Biomass DECIMAL)', |
| 'CREATE TABLE Locations (id INT PRIMARY KEY, name VARCHAR(50), region VARCHAR(50), depth INT)', |
| ] |
| embeddings = model.encode(sentences) |
| print(embeddings.shape) |
| # [3, 1024] |
| |
| # Get the similarity scores for the embeddings |
| similarities = model.similarity(embeddings, embeddings) |
| print(similarities.shape) |
| # [3, 3] |
| ``` |
|
|
| <!-- |
| ### Direct Usage (Transformers) |
|
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| <details><summary>Click to see the direct usage in Transformers</summary> |
|
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| </details> |
| --> |
|
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| <!-- |
| ### Downstream Usage (Sentence Transformers) |
|
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| 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.* |
| --> |
|
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| <!-- |
| ## 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.* |
| --> |
|
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| <!-- |
| ### Recommendations |
|
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| *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
| --> |
|
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| ## Training Details |
|
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| ### Framework Versions |
| - Python: 3.10.14 |
| - Sentence Transformers: 3.0.1 |
| - Transformers: 4.42.3 |
| - PyTorch: 2.3.1+cu121 |
| - Accelerate: 0.31.0 |
| - Datasets: 2.20.0 |
| - Tokenizers: 0.19.1 |
|
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| ## 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 |
|
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| *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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