Model Details
Full Model IDgoogle/embeddinggemma-300m
Pipeline / Tasksentence-similarity
Librarysentence-transformers
Downloads (all-time)2.4M
Likes2.1K
Last Modified9/25/2025
Author / Orggoogle
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("sentence-similarity", model="google/embeddinggemma-300m")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
sentence-transformerssafetensorsgemma3_textsentence-similarityfeature-extractiontext-embeddings-inferencearxiv:2509.20354license:gemmaeval-resultsendpoints_compatibleregion:us
More sentence-similarity Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: sentence-similarity
This model is designed for the sentence-similarity task. Explore more models for this use case.
All sentence-similarity Models →📊 Popularity
⬇ Downloads2.4M
❤️ Community Likes2.1K
🛠️ Requirements
- →Install: pip install sentence-transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.