How to use GrishaKushnir/embeddinggemma-300m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GrishaKushnir/embeddinggemma-300m") 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]
https://huggingface.co/GrishaKushnir/embeddinggemma-300m/resolve/main/notebook.ipynb
hf download hf://GrishaKushnir/embeddinggemma-300m/notebook.ipynb
curl -L -o notebook.ipynb https://huggingface.co/GrishaKushnir/embeddinggemma-300m/resolve/main/notebook.ipynb
