Instructions to use argmaxinc/mlx-stable-diffusion-3.5-large 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 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, 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 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 argmaxinc/mlx-stable-diffusion-3.5-large
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio

- Xet hash:
- 794ece162190da8904252b96f45b4f4e964fb2506ec94ee709fe38010bfd6439
- Size of remote file:
- 1.24 MB
- SHA256:
- 3f079933d989f28fefa258226198e56a5e3dae78458fc63f36f07e9e46a81355
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