Instructions to use diffusers/FLUX.1-dev-torchao-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/FLUX.1-dev-torchao-int8 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-int8", 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
- Xet hash:
- 4af3815330cf5a26e7bac1e0cc8df8a5722663ed8f970134ba6fe8cbcfd43676
- Size of remote file:
- 1.94 GB
- SHA256:
- 9f94fa635af897d12e6cd0b12994d42cfc1b2d69818bda97f6cfb8634a85951d
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