Feature Extraction
MLX
Safetensors
qwen3
apple-silicon
quantized
mixed-precision
axquant
axq
development
MXFP4
embedding
sentence-similarity
4-bit precision
Instructions to use AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4 --local-dir AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download model.safetensors from AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4: direct link, hf CLI and curl.
- Browser
- Download file 399 MB
-
https://huggingface.co/AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4/resolve/main/model.safetensors
- Command line
-
hf download hf://AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP4/resolve/main/model.safetensors
399 MB
- Xet hash:
- dd41c8fc6b3affc4b0d96d8da8ec33cba72752e07f3e206c2f4016f35ca1991a
- Size of remote file:
- 399 MB
- SHA256:
- 304e1bf5200136590adda28f8e160abbcab19ad4880f93fc4d60104dd8815e05
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