Instructions to use xingyoujun/arm_cav2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xingyoujun/arm_cav2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xingyoujun/arm_cav2", 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:
- 5673ff03eed458e8b3c5f113204b77734cb710fdbcbdea8b278650efa822dd9a
- Size of remote file:
- 6.88 GB
- SHA256:
- ac7a7a0c74c7783abb0ae8b93f7470732a1ad45f8149c7a5e5d2d2d2a515c3ed
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