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:
- ea31dc54421854b51c0f2d7c88b5c9f3203c272f46569cc6ff98979afa584e9c
- Size of remote file:
- 60 Bytes
- SHA256:
- 9e8f7a3ce4e41e26223ea64077e952095912526b1cb0fc2a81da5166545aea10
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