Instructions to use argmaxinc/mlx-stable-diffusion-3-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- DiffusionKit
How to use argmaxinc/mlx-stable-diffusion-3-medium 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-medium, 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-medium with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-stable-diffusion-3-medium argmaxinc/mlx-stable-diffusion-3-medium
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio

- Xet hash:
- 34c5ec034e6a8b63480571a4b9093baae29e3bf7ad9621a91a2651f6d3383999
- Size of remote file:
- 1.1 MB
- SHA256:
- f5682ea6a085b28610ec5587301cf675f2cb1ed5e05cf59c0b4d1d4f70e4fc6c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.