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
Add pipeline tag and project page link
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by nielsr HF Staff - opened
README.md
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license: cc-by-nc-4.0
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Models required for
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license: cc-by-nc-4.0
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pipeline_tag: image-to-image
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Models required for [TC-Light: Temporally Consistent Relighting for Dynamic Long Videos](https://huggingface.co/papers/2506.18904).
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Project page: https://dekuliutesla.github.io/tclight/
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