Instructions to use diffusers/FLUX.1-dev-bnb-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/FLUX.1-dev-bnb-8bit 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-bnb-8bit", 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:
- 68709674913d839ec31d6335ad45a562d8914144b019cb95ddd4fffc3d5eb1a1
- Size of remote file:
- 3.04 GB
- SHA256:
- fedb3beecf8465407903bc69908639ac0b2dd723f6babe4bc71c00d6fc0221b7
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