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README.md

@@ -1,3 +1,101 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+- zh
+pipeline_tag: image-to-image
+library_name: diffusers
+---
+
+## 🔥🔥🔥 News!!
+* Sep 08, 2025: 👋 We release [step1x-edit-v1p2-preview](https://huggingface.co/stepfun-ai/Step1X-Edit-v1p2-preview), a new version of Step1X-Edit with reasoning edit ability and better performance (report to be released soon), featuring:
+  - Native Reasoning Edit Model: Combines instruction reasoning with reflective correction to handle complex edits more accurately. Performance on KRIS-Bench:
+    |    Models    |   Factual Knowledge ⬆️   |  Conceptual Knowledge ⬆️ | Procedural Knowledge ⬆️   |  Overall ⬆️ | 
+    |:------------:|:------------:|:------------:| :------------:|:------------:| 
+    | Step1X-Edit v1.1  | 53.05 |  54.34 | 44.66 | 51.59 |   
+    | Step1x-edit-v1p2-preview  | 60.49 | 58.81 | 41.77 | 52.51 | 
+    | Step1x-edit-v1p2-preview (thinking)  | 62.24 | 62.25 | 44.43 | 55.21| 
+    | Step1x-edit-v1p2-preview (thinking + reflection) | 62.94 |  61.82 |  44.08 |  55.64 | 
+  - Improved image editing quality and better instruction-following performance. Performance on GEdit-Bench:
+    |     Models    |     G_SC ⬆️   |  G_PQ ⬆️ | G_O ⬆️   |  Q_SC ⬆️ | Q_PQ ⬆️   |  Q_O ⬆️ |
+    |:------------:|:------------:|:------------:| :------------:|:------------:| :------------:|:------------:|
+    | Step1X-Edit (v1.0)  |    7.13   | 7.00 |   6.44   | 7.39 |    7.28   | 7.07 | 
+    | Step1X-Edit (v1.1)  |    7.66   | 7.35 |   6.97   | 7.65 |    7.41   | 7.35 | 
+    | Step1x-edit-v1p2-preview  |    8.14   | 7.55 |   7.42   | 7.90 |   7.34   | 7.40   |
+<!-- ## Image Edit Demos -->
+
+<div align="center">
+<img width="720" alt="demo" src="assets/image_edit_demo.gif">
+<p><b>Step1X-Edit:</b> a unified image editing model performs impressively on various genuine user instructions. </p>
+</div>
+
+
+## 🧩 Model Usages
+Install the `diffusers` package from the following command:
+```bash
+git clone -b dev/MergeV1-2 https://github.com/Peyton-Chen/diffusers.git
+cd diffusers
+pip install -e .
+```
+
+Here is an example for using the `Step1XEditPipelineV1P2` class to edit images with thinking and reflection:
+
+```python
+import torch
+from diffusers import Step1XEditPipelineV1P2
+from diffusers.utils import load_image
+pipe = Step1XEditPipelineV1P2.from_pretrained("stepfun-ai/Step1X-Edit-v1p2-preview", torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+print("=== processing image ===")
+image = load_image("examples/0000.jpg").convert("RGB")
+prompt = "add a ruby ​​pendant on the girl's neck."
+enable_thinking_mode=True
+enable_reflection_mode=True
+pipe_output = pipe(
+    image=image,
+    prompt=prompt,
+    num_inference_steps=28,
+    true_cfg_scale=4,
+    generator=torch.Generator().manual_seed(42),
+    enable_thinking_mode=enable_thinking_mode,
+    enable_reflection_mode=enable_reflection_mode,
+)
+if enable_thinking_mode:
+    print("Reformat Prompt:", pipe_output.reformat_prompt)
+for image_idx in range(len(pipe_output.images)):
+    pipe_output.images[image_idx].save(f"0001-{image_idx}.jpg", lossless=True)
+    if enable_reflection_mode:
+        print(pipe_output.think_info[image_idx])
+```
+
+The results will look like:
+<div align="center">
+<img width="1080" alt="results" src="assets/results_show.png">
+</div>
+
+
+
+## 📑 Model introduction
+<div align="center">
+<img width="720" alt="demo" src="assets/arch.png">
+</div>
+
+Framework of Step1X-Edit. Step1X-Edit leverages the image understanding capabilities
+of MLLMs to parse editing instructions and generate editing tokens, which are then decoded into
+images using a DiT-based network.More details please refer to our [technical report](https://arxiv.org/abs/2504.17761).
+
+
+We release [GEdit-Bench](https://huggingface.co/datasets/stepfun-ai/GEdit-Bench) as a new benchmark, grounded in real-world usages is developed to support more authentic and comprehensive evaluation. This benchmark, which is carefully curated to reflect actual user editing needs and a wide range of editing scenarios, enables more authentic and comprehensive evaluations of image editing models. Part results of the benchmark are shown below:
+<div align="center">
+<img width="1080" alt="results" src="assets/eval_res_en.png">
+</div>
+
+## Citation
+```
+@article{liu2025step1x-edit,
+      title={Step1X-Edit: A Practical Framework for General Image Editing}, 
+      author={Shiyu Liu and Yucheng Han and Peng Xing and Fukun Yin and Rui Wang and Wei Cheng and Jiaqi Liao and Yingming Wang and Honghao Fu and Chunrui Han and Guopeng Li and Yuang Peng and Quan Sun and Jingwei Wu and Yan Cai and Zheng Ge and Ranchen Ming and Lei Xia and Xianfang Zeng and Yibo Zhu and Binxing Jiao and Xiangyu Zhang and Gang Yu and Daxin Jiang},
+      journal={arXiv preprint arXiv:2504.17761},
+      year={2025}
+}
+```