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
- Draw Things
- DiffusionBee
- Xet hash:
- 8d074d03c89850ac5366bdb6d9bb7798e2197451e375ca0f4c05908b7a3a154d
- Size of remote file:
- 924 MB
- SHA256:
- dd02fa7a1cb4eca2db6ef3e7de5bee468c67497acf3ecd91977e549a96e58dff
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