Sentence Similarity
sentence-transformers
PyTorch
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use cgldo/semanticClone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cgldo/semanticClone with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cgldo/semanticClone") 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
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:4b13b8593311201737b0acaa24f33c39e2d07953e5ba13fc6ff0c6242d13e1b5
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size 670332568
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