Any-to-Any
Transformers
Diffusers
text-to-image
image-editing
image-understanding
vision-language
multimodal
unified-model
Instructions to use Skywork/Unipic3-Consistency-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Skywork/Unipic3-Consistency-Model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Skywork/Unipic3-Consistency-Model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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## 📖 Introduction
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<div align="center"> <img src="unipic3.png" alt="Model Teaser" width="720"> </div>
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**UniPic3-Consistency-Model** is a few-step image editing and multi-image composition model based on **Consistency Flow Matching (CM)**.
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The model learns a *trajectory-consistent* mapping from noisy latent states to clean images, enabling stable generation with strong structural consistency.
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It is distilled from **UniPic-3** to support **fast inference (≤8 steps)** while preserving composition correctness.The model is especially suitable for scenarios requiring **geometric alignment** and **semantic coherence**, such as multi-image composition and human–object interaction (HOI).
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## 📖 Introduction
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<div align="center"> <img src="unipic3.png" alt="Model Teaser" width="720"> </div>
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**UniPic3-Consistency-Model** is a few-step image editing and multi-image composition model based on **Consistency Flow Matching (CM)**.
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The model learns a *trajectory-consistent* mapping from noisy latent states to clean images, enabling stable generation with strong structural consistency.
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It is distilled from **UniPic-3** to support **fast inference (≤8 steps)** while preserving composition correctness.The model is especially suitable for scenarios requiring **geometric alignment** and **semantic coherence**, such as multi-image composition and human–object interaction (HOI).
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