Instructions to use hf-internal-testing/taesd-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/taesd-diffusers 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/taesd-diffusers", 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:
- e7a33e790df6bb129229a5b35ce3bdd7bab40ddacd94f1fe8bdb78341bfbf285
- Size of remote file:
- 9.83 MB
- SHA256:
- 6cf564d324a6dd7f66b9fa2daeb5cdeea479b67502aacd13f71c05abfd8e3737
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