Instructions to use HanjungKim/UniSkill with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HanjungKim/UniSkill with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HanjungKim/UniSkill", 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
Set pipeline tag to robotics
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README.md
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language:
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tags:
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- pytorch
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- robotics
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library_name: diffusers
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base_model:
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- timbrooks/instruct-pix2pix
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<h1> UniSkill: Imitating Human Videos via Cross-Embodiment Skill Representations</h1>
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base_model:
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- timbrooks/instruct-pix2pix
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language:
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- en
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library_name: diffusers
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license: mit
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pipeline_tag: robotics
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tags:
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- pytorch
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- robotics
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---
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<h1> UniSkill: Imitating Human Videos via Cross-Embodiment Skill Representations</h1>
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