Sentence Similarity
sentence-transformers
Safetensors
Korean
xlm-roberta
feature-extraction
korean
legal
retrieval
text-embeddings-inference
Instructions to use ysmeta/EVE-Embed-1.0-Legal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ysmeta/EVE-Embed-1.0-Legal with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ysmeta/EVE-Embed-1.0-Legal") 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
- Xet hash:
- d54c4c5045f8cdb90216c2fba7bba2b10faedfcf646266a6d908ab8518be6562
- Size of remote file:
- 17.1 MB
- SHA256:
- 344e3feb078b84a4c30158f5b85f3dbaeee7a1d2689e0a0a9ebb8a0d63a8faf7
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