Instructions to use thedeoxen/MOSS-Image-pose-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thedeoxen/MOSS-Image-pose-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("thedeoxen/MOSS-Image-pose-controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "OpenMOSS-Team/MOSS-Image-SFT", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Commit History
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Update README.md
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Delete images/curb.jpg
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Match the example prompt to the stance
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Replace the anime pose strip with the chosen stance
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Add a readable dynamic anime pose
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Add a readable dynamic anime pose
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Remove the dance and trio examples
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Remove the dance and trio examples
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Remove the ledge pose example
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Remove the ledge pose example
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Add example strips
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Add example strips
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Use the standard MOSS-Image CLIP, VAE and scheduler names
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Use the standard MOSS-Image CLIP, VAE and scheduler names
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Add control LoRA weights, ComfyUI workflow and model card
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Prepare private model card draft
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initial commit
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