Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
text-embeddings-inference
Eval Results
Instructions to use google/embeddinggemma-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use google/embeddinggemma-300m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("google/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] - Inference
- Notebooks
- Google Colab
- Kaggle
Request: DOI
#26
by zahar24 - opened
1
Hi @zahar24 ,
Welcome to Google's Gemma family of open models, I'm glad for your interest in the Gemma models.
You can access the google/embeddinggemma-300m model using the provided access token or download the model weights for local use in your project. For more information, please visit this link.
For generating access token in HuggingFace, could you please refer this link.
Thanks.