Instructions to use yujiepan/FLUX.1-dev-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yujiepan/FLUX.1-dev-tiny-random with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yujiepan/FLUX.1-dev-tiny-random", 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:
- cc3872fc4168a59170ad55ac9ab822cd3f721fe8b0fa637599a05d40fd2d8d94
- Size of remote file:
- 519 kB
- SHA256:
- 69e2032a0f52db4c7c6c9d5d3c2723f40b74c049fa50d0027dea46ff9e1a9b0f
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