Sentence Similarity
sentence-transformers
Safetensors
greenleaf_embed
embeddings
legal
retrieval
feature-extraction
mteb
mleb
legal-tech
case-law
contracts
judicialmind
custom_code
Instructions to use judicialmind/greenleaf-law-embed-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use judicialmind/greenleaf-law-embed-tiny with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("judicialmind/greenleaf-law-embed-tiny", trust_remote_code=True) 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
- Xet hash:
- 5875f2843096b6a9467c784e51c333835412bfc4cfed1565aaf17410d43dffee
- Size of remote file:
- 11.4 MB
- SHA256:
- 90f07755475023b0eb89035590c08a9cb07640dab5315486fa3a5873999319e7
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