Sentence Similarity
Core ML
sentence-transformers
multilingual
embedding_gemma2
feature-extraction
embeddings
gemma
apple-silicon
Instructions to use shirochenkov90/embeddinggemma-2-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use shirochenkov90/embeddinggemma-2-coreml with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shirochenkov90/embeddinggemma-2-coreml") 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
Ctrl+K
Core ML conversion of google/embeddinggemma-2 (text, full sentence-transformers pipeline, fp16)
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