Sentence Similarity
sentence-transformers
Safetensors
English
German
gemma3_text
feature-extraction
text-embeddings-inference
Instructions to use headwAI/embeddinggemma-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use headwAI/embeddinggemma-300m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("headwAI/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] - Notebooks
- Google Colab
- Kaggle
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# EmbeddingGemma model card
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**Base Model Page** [EmbeddingGemma](https://huggingface.co/google/embeddinggemma-300m)
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**Resources and Technical Documentation**:
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# EmbeddingGemma model card
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**Base Model Page** [EmbeddingGemma Huggingface](https://huggingface.co/google/embeddinggemma-300m)
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**Blog Model Page**: [EmbeddingGemma Blog](https://ai.google.dev/gemma/docs/embeddinggemma)
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**Resources and Technical Documentation**:
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