Instructions to use AnzeZ/fede-embeddinggemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AnzeZ/fede-embeddinggemma with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AnzeZ/fede-embeddinggemma") 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:
- 9abe59178c1065c84a08fda4b8faf2fb03f7abcc6e27ddcb891e461c54ea3a53
- Size of remote file:
- 33.4 MB
- SHA256:
- d6c4c6c7ecda463434a6fafacc071da6de4a1c644d58d2c14de03520ecb8ff32
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