Instructions to use HandEdit/HandEdit-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
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- PEFT
How to use HandEdit/HandEdit-LoRA with PEFT:
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Download README.md from HandEdit/HandEdit-LoRA: direct link, hf CLI and curl.
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- Download file 3.3 kB
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https://huggingface.co/HandEdit/HandEdit-LoRA/resolve/refs%2Fpr%2F1/README.md
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hf download hf://HandEdit/HandEdit-LoRA@refs/pr/1/README.md
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curl -L -o README.md https://huggingface.co/HandEdit/HandEdit-LoRA/resolve/refs%2Fpr%2F1/README.md
3.3 kB
| library_name: peft | |
| tags: | |
| - image-editing | |
| - lora | |
| - robotics | |
| - hand-editing | |
| base_model: | |
| - meituan-longcat/LongCat-Image-Edit | |
| - Shitao/OmniGen-v1 | |
| - black-forest-labs/FLUX.2-klein-base-4B | |
| - stepfun-ai/Step1X-Edit | |
| # HandEdit LoRA | |
| HandEdit provides parameter-efficient LoRA adapters that specialize four | |
| open-source image-editing backbones for human-to-robot-hand replacement. | |
| We build more than 20K aligned training pairs from the HandEdit data. Each pair | |
| contains an input image with a real human hand interacting with an object and a | |
| corresponding target image in which only the hand is replaced by an Inspire | |
| robotic hand. The training instruction asks the model to preserve the original | |
| wrist pose, finger configuration, grasp relation, object contact points, | |
| interaction object, background, lighting, and camera viewpoint as closely as | |
| possible. | |
| Only LoRA parameters are released; the full base-model weights are not | |
| redistributed. | |
| ## Models | |
| | Adapter | Official base model | Local checkpoint | | |
| | --- | --- | --- | | |
| | LongCat-Image-Edit | [`meituan-longcat/LongCat-Image-Edit`](https://huggingface.co/meituan-longcat/LongCat-Image-Edit) | `checkpoints/longcat/` | | |
| | OmniGen-v1 | [`Shitao/OmniGen-v1`](https://huggingface.co/Shitao/OmniGen-v1) | `checkpoints/omnigen/` | | |
| | FLUX.2 Klein Base 4B | [`black-forest-labs/FLUX.2-klein-base-4B`](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-4B) | `checkpoints/flux2/handedit_flux2_klein4b_lora.safetensors` | | |
| | Step1X-Edit | [`stepfun-ai/Step1X-Edit`](https://huggingface.co/stepfun-ai/Step1X-Edit) | `checkpoints/step1x/inspire_step1x_r32_a16_res512.safetensors` | | |
| ## Download | |
| **[Download all four sanitized LoRA checkpoints](https://huggingface.co/HandEdit/HandEdit-LoRA/resolve/main/checkpoints.zip?download=true)** | |
| Or download and verify them from the command line: | |
| ```bash | |
| pip install huggingface_hub | |
| python scripts/download_weights.py | |
| python scripts/verify_weights.py | |
| ``` | |
| The published ZIP and individual adapter files are hosted in | |
| [`HandEdit/HandEdit-LoRA`](https://huggingface.co/HandEdit/HandEdit-LoRA). | |
| ## Inference | |
| Detailed environment setup and commands are in | |
| [`docs/INFERENCE.md`](docs/INFERENCE.md). The shortest examples are: | |
| ```bash | |
| # LongCat-Image-Edit | |
| python scripts/infer_longcat_lora.py \ | |
| --input_dir ./examples/input --output_dir ./outputs/longcat | |
| # OmniGen-v1 | |
| python scripts/infer_omnigen_lora.py \ | |
| --input_dir ./examples/input --output_dir ./outputs/omnigen | |
| # FLUX.2 Klein Base 4B | |
| python scripts/infer_flux2_lora.py \ | |
| --input_dir ./examples/input --output_dir ./outputs/flux2 | |
| # Step1X-Edit | |
| python scripts/infer_step1x_lora.py \ | |
| --repo_dir ./third_party/Step1X-Edit \ | |
| --model_dir ./weights/Step1X-Edit \ | |
| --input_dir ./examples/input --output_dir ./outputs/step1x \ | |
| --quantized --offload | |
| ``` | |
| ## Release hygiene | |
| The public weights are sanitized copies. Training-data identifiers, dataset | |
| sizes, local paths, author fields, timestamps, session information, and other | |
| training-process metadata were removed without changing tensor bytes. See | |
| [`SANITIZATION.md`](SANITIZATION.md) and `weights_manifest.json`. | |
| ## Base-model licenses | |
| Users must follow the license and access terms of each official base model. | |
| This repository does not redistribute the four base models. | |