Sentence Similarity
sentence-transformers
Safetensors
French
bert
feature-extraction
text-embeddings-inference
Instructions to use crazyjeannot/literary_bge_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use crazyjeannot/literary_bge_base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("crazyjeannot/literary_bge_base") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- **Model Type:** Sentence Transformer
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- **Base model:** [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
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- **Maximum Sequence Length:** 512 tokens
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- **Output Dimensionality:** 1024
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- **Similarity Function:** Cosine Similarity
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- **Training Dataset:** [crazyjeannot/fr_literary_dataset_base](https://huggingface.co/datasets/crazyjeannot/fr_literary_dataset_base)
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- **Language:** French
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- **Model Type:** Sentence Transformer
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- **Base model:** [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
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- **Maximum Sequence Length:** 512 tokens
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- **Output Dimensionality:** 1024
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- **Similarity Function:** Cosine Similarity
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- **Training Dataset:** [crazyjeannot/fr_literary_dataset_base](https://huggingface.co/datasets/crazyjeannot/fr_literary_dataset_base)
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- **Language:** French
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