Instructions to use tamikisg/multilingual-e5-small-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tamikisg/multilingual-e5-small-coreml with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tamikisg/multilingual-e5-small-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
Download MultilingualE5Small.mlpackage/Data/com.apple.CoreML/model.mlmodel from tamikisg/multilingual-e5-small-coreml: direct link, hf CLI and curl.
- Browser
- Download file 143 kB
-
https://huggingface.co/tamikisg/multilingual-e5-small-coreml/resolve/main/MultilingualE5Small.mlpackage/Data/com.apple.CoreML/model.mlmodel
- Command line
-
hf download hf://tamikisg/multilingual-e5-small-coreml/MultilingualE5Small.mlpackage/Data/com.apple.CoreML/model.mlmodel
-
curl -L -o model.mlmodel https://huggingface.co/tamikisg/multilingual-e5-small-coreml/resolve/main/MultilingualE5Small.mlpackage/Data/com.apple.CoreML/model.mlmodel
143 kB
- Xet hash:
- ca44cccda8fd47593e8f5e81343c22fc4d28e49eb7d04093455e5e446dde9f4a
- Size of remote file:
- 143 kB
- SHA256:
- 00155ee760470932d9838bc6fefc817a48c78a15692e73aa799dd3bd853b0fbb
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