Instructions to use Roxas13/e5-small-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Roxas13/e5-small-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir e5-small-mlx Roxas13/e5-small-mlx
- sentence-transformers
How to use Roxas13/e5-small-mlx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Roxas13/e5-small-mlx") 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
- Local Apps Settings
- LM Studio
- Xet hash:
- aba0c1033729270fad2b554379207c25367c7fda3a863829fe2b89c13754e2c1
- Size of remote file:
- 17.1 MB
- SHA256:
- 642eede941e22781e8b3c9a2dfe2015027b2fd855410b16cd66f07b0f3c76641
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