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 model.safetensors from noname002/embeddinggemma-300m-greennode-5fre: direct link, hf CLI and curl.
- Browser
- Download file 457 MB
-
https://huggingface.co/noname002/embeddinggemma-300m-greennode-5fre/resolve/main/model.safetensors
- Command line
-
hf download hf://noname002/embeddinggemma-300m-greennode-5fre/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/noname002/embeddinggemma-300m-greennode-5fre/resolve/main/model.safetensors
457 MB
- Xet hash:
- 193310b26d143a688268ecf646967e2e0f51789ce8a48137972ca8c5f88d0654
- Size of remote file:
- 457 MB
- SHA256:
- 2b4d53d23c1d2821f64601c8234cc9952ca24ed595612b6692437728bbfc3bad
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