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
#5
by sinahb - opened
hi.
i need this model for test my rag project
thanks
Hi @sinahb ,
Welcome to Google's Gemma family of open source 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.
Initially you have to provide the Grant in the model's model card page.
For generating access token in HuggingFace, could you please refer this link, please reach out to me if you required any additional assistance.
Thanks.
Hi, can I download this model locally so I don't have to download it every time?
