Instructions to use argmaxinc/mlx-stable-diffusion-3.5-large-4bit-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- DiffusionKit
How to use argmaxinc/mlx-stable-diffusion-3.5-large-4bit-quantized with DiffusionKit:
# Pipeline for Stable Diffusion 3 from diffusionkit.mlx import DiffusionPipeline pipeline = DiffusionPipeline( shift=3.0, use_t5=False, model_version=argmaxinc/mlx-stable-diffusion-3.5-large-4bit-quantized, low_memory_mode=True, a16=True, w16=True, )
# Image Generation HEIGHT = 512 WIDTH = 512 NUM_STEPS = 50 CFG_WEIGHT = 5 image, _ = pipeline.generate_image( "a photo of a cat", cfg_weight=CFG_WEIGHT, num_steps=NUM_STEPS, latent_size=(HEIGHT // 8, WIDTH // 8), )
- MLX
How to use argmaxinc/mlx-stable-diffusion-3.5-large-4bit-quantized with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-stable-diffusion-3.5-large-4bit-quantized argmaxinc/mlx-stable-diffusion-3.5-large-4bit-quantized
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
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# Stable Diffusion 3
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## Check out the [original model](https://huggingface.co/stabilityai/stable-diffusion-3.5-large)!
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## Check out the [DiffusionKit](https://github.com/argmaxinc/DiffusionKit) github repository!
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# Stable Diffusion 3.5 Large Quantized on DiffusionKit MLX!
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This checkpoint was generated by applying [`nn.quantize`](https://ml-explore.github.io/mlx/build/html/python/_autosummary/mlx.nn.quantize.html#mlx.nn.quantize) to all linear layers of MMDiT
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## Check out the [original model](https://huggingface.co/stabilityai/stable-diffusion-3.5-large)!
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## Check out the [DiffusionKit](https://github.com/argmaxinc/DiffusionKit) github repository!
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