Instructions to use jschoormans/control_pose_diff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jschoormans/control_pose_diff with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jschoormans/control_pose_diff", 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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- fa730f8172844250367b9cd6eaa3d6b35eb88de0d8d7d3390354e61ffa36f3cf
- Size of remote file:
- 1.45 GB
- SHA256:
- f80976c360195f969b4cad79f93422f1442ca9a6617685fd0154448805afd3d7
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