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InstantCharacter is a tuning-free diffusion transformer framework created by Tencent Hunyuan / InstantX team, which enables generating images of a specific character (subject) from a single reference image, preserving identity and character features. Uses adapters, so full fine-tuning of the base model is not required. Demo scripts and pipeline API (via infer_demo.py, pipeline.py) included. It works by adapting a base image generation model with a lightweight adapter so that you can produce character-preserving generations in various downstream tasks (e.g. changing pose, clothing, scene) without needing full model fine-tuning. Works with huggingface/transformers/diffusers ecosystems.
Features
- Tuning-free: uses adapters, so full fine-tuning of the base model is not required
- Preserves character identity from a single reference image
- Supports style customization (e.g. via LoRA style adapters)
- Offload inference for reduced VRAM usage (works under ~22GB VRAM)
- Demo scripts and pipeline API (via infer_demo.py, pipeline.py) included
- Works with huggingface / transformers / diffusers ecosystems
Project Samples
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