Instructions to use amd/FLUX.1-schnell_io32_amdgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use amd/FLUX.1-schnell_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-schnell_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 Settings
- Draw Things
- DiffusionBee
Download sample.png from amd/FLUX.1-schnell_io32_amdgpu: direct link, hf CLI and curl.
- Browser
- Download file 1.64 MB
-
https://huggingface.co/amd/FLUX.1-schnell_io32_amdgpu/resolve/main/sample.png
- Command line
-
hf download hf://amd/FLUX.1-schnell_io32_amdgpu/sample.png
-
curl -L -o sample.png https://huggingface.co/amd/FLUX.1-schnell_io32_amdgpu/resolve/main/sample.png
1.64 MB

- Xet hash:
- 42f56635c3af25aa942b423b7a0ff21a44071c1c7baebe7e15f77c09a2f9fdbc
- Size of remote file:
- 1.64 MB
- SHA256:
- ea4bc556967282d5feafec81322efb03a0be9b3b5b88867db4fad80ad4d2304b
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