Instructions to use tiny-random/flux2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tiny-random/flux2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tiny-random/flux2", 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:
- b0e5f32fd3706c8e38700918b97af35fe8cb933a261e3edf373e5ce9c80c584a
- Size of remote file:
- 876 kB
- SHA256:
- 37a00f9d489b66b9e670d826e0db2ff1df7b2c02b3f27ab55fcad46af2e662fa
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