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:
- da02c39c525d6a0b2ee7f8b84c7284b4e59c51b4a76706f00cf83e1823b23d79
- Size of remote file:
- 1.79 MB
- SHA256:
- 1a507135b2c221ad7d103beb2087db06ed965f2c787cd85d8ee2614d4b21ca5d
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