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
Add onnx model
#14
by wirthual - opened
Add onnx model
wirthual changed pull request title from onnx to Add onnx model
wirthual changed pull request status to open
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("google/embeddinggemma-300m", backend="onnx",revision="refs/pr/14")
sentences = ["This is an example sentence", "Each sentence is converted"]
embeddings = model.encode(sentences)
print(embeddings)