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NOTICE

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+Copyright (C) 2025 AIDC-AI
+Licensed under the Apache License, Version 2.0 (the "License").
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+This model was trained based on the following model:
+stable-diffusion-xl-base-1.0 (https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0), license: CreativeML Open RAIL++-M License (https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md). 
+Copyright (c) 2023 Stability AI CreativeML Open RAIL++-M License dated July 26, 2023
+Section I: PREAMBLE Multimodal generative models are being widely adopted and used, and have the potential to transform the way artists, among other individuals, conceive and benefit from AI or ML technologies as a tool for content creation. Notwithstanding the current and potential benefits that these artifacts can bring to society at large, there are also concerns about potential misuses of them, either due to their technical limitations or ethical considerations. In short, this license strives for both the open and responsible downstream use of the accompanying model. When it comes to the open character, we took inspiration from open source permissive licenses regarding the grant of IP rights. Referring to the downstream responsible use, we added use-based restrictions not permitting the use of the model in very specific scenarios, in order for the licensor to be able to enforce the license in case potential misuses of the Model may occur. 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+Section IV: OTHER PROVISIONS Updates and Runtime Restrictions. To the maximum extent permitted by law, Licensor reserves the right to restrict (remotely or otherwise) usage of the Model in violation of this License. Trademarks and related. Nothing in this License permits You to make use of Licensors’ trademarks, trade names, logos or to otherwise suggest endorsement or misrepresent the relationship between the parties; and any rights not expressly granted herein are reserved by the Licensors. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Model and the Complementary Material (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Model, Derivatives of the Model, and the Complementary Material and assume any risks associated with Your exercise of permissions under this License. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Model and the Complementary Material (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. Accepting Warranty or Additional Liability. While redistributing the Model, Derivatives of the Model and the Complementary Material thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. If any provision of this License is held to be invalid, illegal or unenforceable, the remaining provisions shall be unaffected thereby and remain valid as if such provision had not been set forth herein.
+END OF TERMS AND CONDITIONS
+Attachment A Use Restrictions You agree not to use the Model or Derivatives of the Model: In any way that violates any applicable national, federal, state, local or international law or regulation; For the purpose of exploiting, harming or attempting to exploit or harm minors in any way; To generate or disseminate verifiably false information and/or content with the purpose of harming others; To generate or disseminate personal identifiable information that can be used to harm an individual; To defame, disparage or otherwise harass others; For fully automated decision making that adversely impacts an individual’s legal rights or otherwise creates or modifies a binding, enforceable obligation; For any use intended to or which has the effect of discriminating against or harming individuals or groups based on online or offline social behavior or known or predicted personal or personality characteristics; To exploit any of the vulnerabilities of a specific group of persons based on their age, social, physical or mental characteristics, in order to materially distort the behavior of a person pertaining to that group in a manner that causes or is likely to cause that person or another person physical or psychological harm; For any use intended to or which has the effect of discriminating against individuals or groups based on legally protected characteristics or categories; To provide medical advice and medical results interpretation; To generate or disseminate information for the purpose to be used for administration of justice, law enforcement, immigration or asylum processes, such as predicting an individual will commit fraud/crime commitment (e.g. by text profiling, drawing causal relationships between assertions made in documents, indiscriminate and arbitrarily-targeted use).

README.md

@@ -1,3 +1,130 @@
----
-license: apache-2.0
----
+# CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation (ICML2025)
+
+<p align="center"> 
+📝 <a href="https://arxiv.org/abs/2502.12579" target="_blank">Paper</a>  • 💡 <a href="https://zhuanlan.zhihu.com/p/1904156278621737628" target="_blank">知乎</a> • 🤗 <a href="https://huggingface.co/AIDC-AI/CHATS" target="_blank">HF Repo</a> 
+</p>
+
+CHATS is a next-generation framework that unifies human preference alignment with classifier-free guidance by modeling both preferred and dispreferred distributions and using a proxy-prompt-based sampling strategy for superior text–image alignment, fidelity, and aesthetic consistency. See the images generated below for examples.
+
+
+<figure>
+  <img src="qualitative_imgs.jpg" alt="CHATS results">
+  <figcaption style="text-align: center;">Generation examples using CHATS (cf. Fig.1 in our paper).</figcaption>
+</figure>
+
+---
+
+## 🚀 Key Features
+
+- **Human-Aligned Fine-Tuning with CFG Integration**  
+  We integrate human preference alignment with classifier-free guidance sampling into a unified framework.
+
+- **Proxy-Prompt Sampling**  
+  Leverage useful signals from both preferred and dispreferred distributions at test time.
+
+- **Data Efficiency**  
+  State-of-the-art results across benchmarks with minimal fine-tuning effort on a small, high-quality dataset.
+
+- **Plug-and-Play**  
+  Compatible with any diffusion backbone and existing guidance methods.
+
+---
+
+## 📦 Installation
+
+```bash
+git clone https://github.com/AIDC-AI/CHATS.git
+cd CHATS
+pip install -r requirements.txt
+
+```
+
+## 📂 Model Checkpoints
+
+We provide pretrained CHATS checkpoints on SDXL for easy download and evaluation:
+ 
+- **Model Repository**: [![Hugging Face](https://img.shields.io/badge/Hugging%20Face-CHATS-blue?logo=Huggingface)](https://huggingface.co/AIDC-AI/CHATS)
+
+
+## 🛠️ Quick Start
+
+```python
+from pipeline import ChatsSDXLPipeline
+
+# Load CHATS-SDXL pipeline
+pipe = ChatsSDXLPipeline.from_pretrained(
+        "AIDC-AI/CHATS",
+        torch_dtype=torch.bfloat16
+    ).to("cuda")
+
+# Generate images
+images = pipe(
+    prompts=["A serene mountain lake at sunset"],
+    num_inference_steps=50,
+    guidance_scale=5,
+    seed=0
+)
+
+# 4. Save outputs
+for i, img in enumerate(images):
+    img.save(f"output_{i}.png")
+```
+
+## 🏋️ Training
+
+To train CHATS from scratch or fine-tune on your own data, run:
+
+```bash
+accelerate launch --config_file=config/ac_ds_8gpu_zero0.yaml  train.py \
+        --pretrained_model_name_or_path=stabilityai/stable-diffusion-xl-base-1.0 \
+        --pretrained_vae_model_name_or_path=madebyollin/sdxl-vae-fp16-fix \
+        --resolution=1024 \
+        --dataloader_num_workers 16 \
+        --train_batch_size=1 \
+        --gradient_accumulation_steps=16 \
+        --max_train_steps=6000 \
+        --learning_rate=3e-09 --scale_lr --lr_scheduler=constant_with_warmup --lr_warmup_steps=100 \
+        --mixed_precision=bf16 \
+        --allow_tf32 \
+        --checkpointing_steps=100 \
+        --output_dir=output \
+        --resume_from_checkpoint latest \
+        --use_adafactor \
+        --gradient_checkpointing \
+        --dataset_name=data-is-better-together/open-image-preferences-v1-binarized \
+```
+
+### Args:
+- config_file: This DeepSpeed parameter allows you to specify the configuration file. If you wish to adjust the number of GPUs used for training, simply change the value of **num_processes** in the ac_ds_xgpu_zero0.yaml file to reflect the desired GPU count.
+- pretrained_model_name_or_path: name or patch of unet model to load
+- pretrained_vae_model_name_or_path: v=name or patch of vae model to load
+- max_train_steps: max steps to train_batch_size
+- output: output dir
+- dataset_name: the huggingface sufix of the selected dataset (e.g. OIP)
+
+
+
+## 📚 Citation
+
+If you use CHATS, please cite our ICML 2025 paper:
+
+```bibtex
+@inproceedings{fu2025chats,
+title={CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation},
+author={Fu, Minghao and Wang, Guo-Hua and Cao, Liangfu and Chen, Qing-Guo and Xu, Zhao and Luo, Weihua and Zhang, Kaifu},
+booktitle={International Conference on Machine Learning (ICML)},
+year={2025}
+}
+```
+
+## 🙏 Acknowledgments
+
+The code is built upon [DiffusionDPO](https://github.com/SalesforceAIResearch/DiffusionDPO), [Diffusers](https://github.com/huggingface/diffusers), and [Transformers](https://github.com/huggingface/transformers).
+
+## 📄 License
+
+The project is released under Apache License 2.0 (http://www.apache.org/licenses/LICENSE-2.0, SPDX-License-identifier: Apache-2.0).
+
+## 🚨 Disclaimer
+
+We used compliance checking algorithms during the training process, to ensure the compliance of the trained model to the best of our ability. Due to complex data and the diversity of language model usage scenarios, we cannot guarantee that the model is completely free of copyright issues or improper content. If you believe anything infringes on your rights or generates improper content, please contact us, and we will promptly address the matter.

Use Restrictions

@@ -0,0 +1,2 @@
+Use Restrictions 
+You agree not to use the Model or Derivatives of the Model: In any way that violates any applicable national, federal, state, local or international law or regulation; For the purpose of exploiting, harming or attempting to exploit or harm minors in any way; To generate or disseminate verifiably false information and/or content with the purpose of harming others; To generate or disseminate personal identifiable information that can be used to harm an individual; To defame, disparage or otherwise harass others; For fully automated decision making that adversely impacts an individual’s legal rights or otherwise creates or modifies a binding, enforceable obligation; For any use intended to or which has the effect of discriminating against or harming individuals or groups based on online or offline social behavior or known or predicted personal or personality characteristics; To exploit any of the vulnerabilities of a specific group of persons based on their age, social, physical or mental characteristics, in order to materially distort the behavior of a person pertaining to that group in a manner that causes or is likely to cause that person or another person physical or psychological harm; For any use intended to or which has the effect of discriminating against individuals or groups based on legally protected characteristics or categories; To provide medical advice and medical results interpretation; To generate or disseminate information for the purpose to be used for administration of justice, law enforcement, immigration or asylum processes, such as predicting an individual will commit fraud/crime commitment (e.g. by text profiling, drawing causal relationships between assertions made in documents, indiscriminate and arbitrarily-targeted use).

model_index.json

@@ -0,0 +1,36 @@
+{
+  "_class_name": "ChatsSDXLPipeline",
+  "_diffusers_version": "0.31.0",
+  "scheduler": [
+    "diffusers",
+    "EulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_two": [
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