Instructions to use tsync-co/anime-80s-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tsync-co/anime-80s-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tsync-co/anime-80s-test", 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:
- bd26ecc14b300a9336d24d8dfbe94f7e8223017197756b5cc202c9914361e71b
- Size of remote file:
- 51.1 MB
- SHA256:
- 5b82dbec444747723fa547bbb1abaa2c19ba380978a6a15acd4924857abdf564
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