Instructions to use diffusers/FLUX.1-dev-torchao-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/FLUX.1-dev-torchao-int4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/FLUX.1-dev-torchao-int4", 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
- Draw Things
- DiffusionBee
- Xet hash:
- ee27a6bd9a007a239506a8e94cf4c58e565feda8cc69c52f6719a749bd535486
- Size of remote file:
- 168 MB
- SHA256:
- 0342412f8dea7f67631fb08ce005c52cc331bded09bf994b02ef3ab4ece43e54
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