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:
- 9590ac14fe761e9cca3964a54774d4a6fabd843b24c60f2793593dcd39d60749
- Size of remote file:
- 72.2 kB
- SHA256:
- cf27b4f52d7eba6b4bc85910b52563793f8fb38d8d4a58020f8cf2c178010062
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