Sentence Similarity
sentence-transformers
Safetensors
Azerbaijani
bert
feature-extraction
retrieval
azerbaijani
embedding
Eval Results (legacy)
text-embeddings-inference
Instructions to use LocalDoc/LocRet-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LocalDoc/LocRet-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LocalDoc/LocRet-small") 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 config_sentence_transformers.json
Browse files
config_sentence_transformers.json
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"pytorch": "2.10.0+cu130"
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"prompts": {
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"query": "",
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"document": ""
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"default_prompt_name":
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"similarity_fn_name": "cosine"
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}
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"pytorch": "2.10.0+cu130"
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"prompts": {
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"query": "query: ",
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"document": "passage: "
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"default_prompt_name": "document",
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"similarity_fn_name": "cosine"
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}
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