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:
- 79b0f7ec2cf983f99083d2edea538c5799da9232c15ef6d5afb94682393e3da4
- Size of remote file:
- 198 MB
- SHA256:
- b7851af2be3f720d2e383974f0421a9a0ea7d5c6863cb23c1f001d5847d31c40
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