Instructions to use mit-han-lab/svdq-int4-flux.1-schnell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mit-han-lab/svdq-int4-flux.1-schnell with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mit-han-lab/svdq-int4-flux.1-schnell", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 46e065d0d888f04147d423742cd6ed6d6c0025cdb2ccd5c005c62d37e4300a39
- Size of remote file:
- 108 MB
- SHA256:
- 379c4cdf19bb03b90290a47b685d6ff4bad82089053de0c96bd4a7560860b1ce
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