Instructions to use hf-internal-testing/tiny-dit-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-dit-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-dit-pipe", 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
- Xet hash:
- 5f994afb1ba18da989cc34090d1b39ebc55a6b1af08900848dd62f0f1e7cc683
- Size of remote file:
- 222 kB
- SHA256:
- 0727ec76d3d32cc3d8652dae37ca9479cbafca076284bba92d3006e4fc55713c
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