Instructions to use Kalvis66/chiptunes_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kalvis66/chiptunes_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("Kalvis66/chiptunes_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:
- 3c041456371b6a5c7b0716ff36a36b5fdcd8777e7061f3c6d0a0bf5bda298f39
- Size of remote file:
- 455 MB
- SHA256:
- 0fcded9f9d9f114d2d04d230e6f67b5d11ca733ec3a95ff5a3f96b38145ea544
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