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 assets/Qwen-Image-2.1-Benchmark.png from abenzerps/Qwen-Image-2.1-Turbo-Quantized: direct link, hf CLI and curl.
- Browser
- Download file 270 kB
-
https://huggingface.co/abenzerps/Qwen-Image-2.1-Turbo-Quantized/resolve/main/assets/Qwen-Image-2.1-Benchmark.png
- Command line
-
hf download hf://abenzerps/Qwen-Image-2.1-Turbo-Quantized/assets/Qwen-Image-2.1-Benchmark.png
-
curl -L -o Qwen-Image-2.1-Benchmark.png https://huggingface.co/abenzerps/Qwen-Image-2.1-Turbo-Quantized/resolve/main/assets/Qwen-Image-2.1-Benchmark.png
270 kB

- Xet hash:
- 4e3b15808fc0ae1f1b4f6d36d7093a385e82c1629766cded03681b3bd2b848e7
- Size of remote file:
- 270 kB
- SHA256:
- 66a1481f7e03491f42ecc0dc2380afdb97e6144759900317be857696e7038ac5
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