Sentence Similarity
sentence-transformers
Safetensors
English
mteb
Sentence Transformers
Eval Results (legacy)
Instructions to use cjell/text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cjell/text with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cjell/text") 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:
- 9975c8d1b126a65f3a73a066a3ff28f98d1cee42c853e8cd5c57c15ef4a349df
- Size of remote file:
- 313 Bytes
- SHA256:
- 1fffd946c5ccd46f2391f7f455fb68d0a2d7f3832d21a93899c1249eeccfb989
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