Feature Extraction
MLX
Safetensors
qwen3
embeddings
sentence-similarity
quantization
omlx
q8
8-bit precision
Instructions to use TiGa-RCE/Qwen3-Embedding-0.6B-MLX-Q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TiGa-RCE/Qwen3-Embedding-0.6B-MLX-Q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3-Embedding-0.6B-MLX-Q8 TiGa-RCE/Qwen3-Embedding-0.6B-MLX-Q8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 515ea6325c7f0723b7c1344a3fd2f2abd6630970b2d54bf56aee18e43da5f6f9
- Size of remote file:
- 11.4 MB
- SHA256:
- 93623af029cdc69b87f2864d3b2cc2424fdf16684f15e139b5b9d08ec34ced91
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