Instructions to use NoesisLab/Collins-Embedding-3M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NoesisLab/Collins-Embedding-3M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NoesisLab/Collins-Embedding-3M") 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:
- 7a0b3aeeb370c970a911ab1fe9f2fa1dd5d6438dce03ec42059c0a6390209749
- Size of remote file:
- 12.5 MB
- SHA256:
- c703775717ef9e52d8dba2441f5df63020ba0ead4e22e070e055f54890624a3d
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