Instructions to use TeslaYang123/TC-Light with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TeslaYang123/TC-Light with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TeslaYang123/TC-Light", 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:
- 35f330d585ec4996335d1ad8282a2198f323108af70dd157792865da68e69130
- Size of remote file:
- 25.4 MB
- SHA256:
- 694cc33c1ac5945798aaf001e7b26a7966a01873879b6d03e5f3d54c97e28d36
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