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:
- b054a03679bdcf89e9eb061bccf7a98de67d05bc86a0e890899f8e4ea99daa62
- Size of remote file:
- 9.79 MB
- SHA256:
- afc4dc0f168f575a92d6a5115dd8dd05bb7b30c393793d67a47250716a1d9478
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