Instructions to use abenzerps/Qwen-Image-2.1-Turbo-Quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use abenzerps/Qwen-Image-2.1-Turbo-Quantized with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download abenzerps/Qwen-Image-2.1-Turbo-Quantized --local-dir Qwen-Image-2.1-Turbo-Quantized
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download qwen-image-2.1-turbo-MLX-4bit.safetensors from abenzerps/Qwen-Image-2.1-Turbo-Quantized: direct link, hf CLI and curl.
- Browser
- Download file 4 GB
-
https://huggingface.co/abenzerps/Qwen-Image-2.1-Turbo-Quantized/resolve/main/qwen-image-2.1-turbo-MLX-4bit.safetensors
- Command line
-
hf download hf://abenzerps/Qwen-Image-2.1-Turbo-Quantized/qwen-image-2.1-turbo-MLX-4bit.safetensors
-
curl -L -o qwen-image-2.1-turbo-MLX-4bit.safetensors https://huggingface.co/abenzerps/Qwen-Image-2.1-Turbo-Quantized/resolve/main/qwen-image-2.1-turbo-MLX-4bit.safetensors
4 GB
- Xet hash:
- 298ae633716917e1291eb2b96585a32a9d2aaefcb97aa770b8778d1c5efef2b0
- Size of remote file:
- 4 GB
- SHA256:
- 9fa538a801ba8d35c670a10f03a5b35a20f049c786fbc06ed0bf4fc3b8058133
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