Instructions to use argmaxinc/mlx-FLUX.1-schnell-4bit-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- DiffusionKit
How to use argmaxinc/mlx-FLUX.1-schnell-4bit-quantized with DiffusionKit:
# Pipeline for Flux from diffusionkit.mlx import FluxPipeline pipeline = FluxPipeline( shift=1.0, model_version=argmaxinc/mlx-FLUX.1-schnell-4bit-quantized, low_memory_mode=True, a16=True, w16=True, )
# Image Generation HEIGHT = 512 WIDTH = 512 NUM_STEPS = 4 CFG_WEIGHT = 0 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-FLUX.1-schnell-4bit-quantized with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-FLUX.1-schnell-4bit-quantized argmaxinc/mlx-FLUX.1-schnell-4bit-quantized
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
Install & run this model easily using llmpm
#9 opened 2 months ago
by
sarthak-saxena
running with python?
1
#8 opened about 1 year ago
by
Retolito
how to use comfyui?
1
#7 opened over 1 year ago
by
srsuzume
Hardware requirements
1
#5 opened over 1 year ago
by
fromjon