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
Core ML conversion of google/embeddinggemma-2 (text, full sentence-transformers pipeline, fp16)
d38f20d verified Download embeddinggemma-2.mlpackage/Data/com.apple.CoreML/model.mlmodel from shirochenkov90/embeddinggemma-2-coreml: direct link, hf CLI and curl.
- Browser
- Download file 916 kB
-
https://huggingface.co/shirochenkov90/embeddinggemma-2-coreml/resolve/main/embeddinggemma-2.mlpackage/Data/com.apple.CoreML/model.mlmodel
- Command line
-
hf download hf://shirochenkov90/embeddinggemma-2-coreml/embeddinggemma-2.mlpackage/Data/com.apple.CoreML/model.mlmodel
-
curl -L -o model.mlmodel https://huggingface.co/shirochenkov90/embeddinggemma-2-coreml/resolve/main/embeddinggemma-2.mlpackage/Data/com.apple.CoreML/model.mlmodel
916 kB
- Xet hash:
- d7329996277926631e2b6396183c9b41f3724e56d459600593b06e1ac0f2f827
- Size of remote file:
- 916 kB
- SHA256:
- ffa86aa150dcfa8185821a8a045f6cecf0ec72c1cbd5b57271b1d16791e11ac7
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