Instructions to use PierrunoYT/taef1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PierrunoYT/taef1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PierrunoYT/taef1", torch_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:
- f4018793cfc1537b54e2fab0c02e32f7e805bf7277e54cc515872e4bfee46413
- Size of remote file:
- 9.88 MB
- SHA256:
- 96cfac57ad0d2314b0bd78065b97266063196ee65cfc082a85be4abb9c89915c
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