Instructions to use diffusers/FLUX.1-dev-torchao-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/FLUX.1-dev-torchao-fp8 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-fp8", 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:
- 523757c3049c44ec8388c793edc5940977ccb5ff4375ac61af7418d6e50f2660
- Size of remote file:
- 168 MB
- SHA256:
- 71626130e357339cfff205609e41df5576b10274702aebed2e00656192b1c61a
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