Feature Extraction
sentence-transformers
Safetensors
multilingual
embedding_gemma2
embedding
sentence-similarity
code
Instructions to use jayyun98/embeddinggemma-2-text-270m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jayyun98/embeddinggemma-2-text-270m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jayyun98/embeddinggemma-2-text-270m") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Commit History
30 days ago
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Add verified BF16 export with unused modality encoders removed
Verified signatureRetained tensors exactly match google/embeddinggemma-2 at revision 914f7f89142e33e77833254d9c9b90c3cef7303b. Includes conversion receipt, CPU FP32 inference equivalence results, usage examples, Apache 2.0 license and attribution.92ad4fa