Instructions to use bhavyagiri/InLegal-Sbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bhavyagiri/InLegal-Sbert with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bhavyagiri/InLegal-Sbert") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- 2_Dense/model.safetensors +3 -0
- model.safetensors +3 -0
2_Dense/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c4fa246b5abf7dce52c3b36cf997c877e143c69d3b39ba11562e6483a314c751
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size 2362560
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e4850c6f4d657aef2a66a03adf79f5c4a269c1b63158e25386102264eba158b7
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size 437951328
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