Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
text-embeddings-inference
Instructions to use noname002/embeddinggemma-300m-greennode-5fre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use noname002/embeddinggemma-300m-greennode-5fre with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("noname002/embeddinggemma-300m-greennode-5fre") 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
Download 2_Dense/model.safetensors from noname002/embeddinggemma-300m-greennode-5fre: direct link, hf CLI and curl.
- Browser
- Download file 9.44 MB
-
https://huggingface.co/noname002/embeddinggemma-300m-greennode-5fre/resolve/main/2_Dense/model.safetensors
- Command line
-
hf download hf://noname002/embeddinggemma-300m-greennode-5fre/2_Dense/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/noname002/embeddinggemma-300m-greennode-5fre/resolve/main/2_Dense/model.safetensors
9.44 MB
- Xet hash:
- f0c1c47d336fb258ab1e1227a197d6c681b8b15256a1d3d28991a08bee7210b5
- Size of remote file:
- 9.44 MB
- SHA256:
- c327f2acb00149676ade24a75e11eb6ebbd367f9ee050267ba56829d2979f702
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