Update README.md

README.md

@@ -1,3 +1,82 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- video-text-to-text
+- question-answering
+language:
+- en
+size_categories:
+- 1K<n<10K
+---
+
+# LiFT: Leveraging Human Feedback for Text-to-Video Model Alignment
+
+## Summary
+This is the dataset proposed in our paper "LiFT: Leveraging Human Feedback for Text-to-Video Model Alignment". LiFT-HRA is a high-quality Human Preference Annotation dataset that can be used to train video-text-to-text reward models. All videos in the LiFT-HRA dataset have resolutions of at least 512×512.
+
+Project: https://codegoat24.github.io/LiFT/
+
+Code: https://github.com/CodeGoat24/LiFT
+
+## Directory
+```
+DATA_PATH
+└─ LiFT-HRA-data.json
+└─ videos
+    └─ HRA_part0.zip
+    └─ HRA_part1.zip
+    └─ HRA_part2.zip
+```
+
+## Usage
+### Installation
+
+1. Clone the github repository and navigate to LiFT folder
+```bash
+git clone https://github.com/CodeGoat24/LiFT.git
+cd LiFT
+```
+2. Install packages
+```
+bash ./environment_setup.sh lift
+```
+
+### Training
+
+**Dataset**
+
+Please download this LiFT-HRA dataset and put it under `./dataset` directory. The data structure is like this:
+```
+dataset
+├── LiFT-HRA
+│  ├── LiFT-HRA-data.json
+│  ├── videos
+```
+
+**Training**
+
+LiFT-Critic-13b
+```bash
+bash LiFT_Critic/train/train_critic_13b.sh
+```
+LiFT-Critic-40b
+```bash
+bash LiFT_Critic/train/train_critic_40b.sh
+```
+
+
+## Model Weights
+We provide pre-trained model weights LiFT-Critic on our LiFT-HRA dataset. Please refer to [here](https://huggingface.co/collections/Fudan-FUXI/lift-6756e628d83c390221e02857).
+
+
+## Citation
+If you find our dataset helpful, please cite our paper.
+
+```bibtex
+@article{LiFT,
+  title={LiFT: Leveraging Human Feedback for Text-to-Video Model Alignment.},
+  author={Wang, Yibin and Tan, Zhiyu, and Wang, Junyan and Yang, Xiaomeng and Jin, Cheng and Li, Hao},
+  journal={arXiv preprint arXiv:2412.04814},
+  year={2024}
+}
+```