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 Settings
- Draw Things
- DiffusionBee
Download controlnet/diffusion_pytorch_model.bin from jschoormans/control_pose_diff: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/jschoormans/control_pose_diff/resolve/main/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://jschoormans/control_pose_diff/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/jschoormans/control_pose_diff/resolve/main/controlnet/diffusion_pytorch_model.bin
1.45 GB
- Xet hash:
- fa730f8172844250367b9cd6eaa3d6b35eb88de0d8d7d3390354e61ffa36f3cf
- Size of remote file:
- 1.45 GB
- SHA256:
- f80976c360195f969b4cad79f93422f1442ca9a6617685fd0154448805afd3d7
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