Instructions to use Lin231/pose1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lin231/pose1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lin231/pose1", 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:
- 8125b8b965e23a86e2d489c50a148132e478f6048dd72708879d07301fe41049
- Size of remote file:
- 1.45 GB
- SHA256:
- 4068293b5d0700d6fbb6f5144257ff649699177af2f9c30401e6191ed2222fd2
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