Instructions to use amd/FLUX.1-dev_io32_amdgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use amd/FLUX.1-dev_io32_amdgpu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("amd/FLUX.1-dev_io32_amdgpu", 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:
- 700f9f7aaf10982acdf610665f8c4103ad1aa055961c1c50d0eb431e822c6b9d
- Size of remote file:
- 528 kB
- SHA256:
- 7311de30896c46419394de3e0f1f0166d36a0e1cd0b2fde4ae1e1536653dde6b
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