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README.md

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+# AccVideo: Accelerating Video Diffusion Model with Synthetic Dataset
+
+This repository contains the pre-trained weights of [AccVideo](). AccVideo is a novel efficient distillation method to accelerate video diffusion models with synthetic datset. Our method is 8.5x faster than HunyuanVideo.
+
+
+[![arXiv](https://img.shields.io/badge/)]()[![Project Page](https://img.shields.io/badge/Project-Website-green)](https://aejion.github.io/accvideo/)
+
+## 🔥🔥🔥 News
+
+* Mar, 2025: We release the inference code and model weights of AccVideo.
+
+
+
+## 📑 Open-source Plan
+
+- [x] Inference 
+- [x] Checkpoints
+- [ ] Multi-GPU Inference
+- [ ] Synthetic Video Dataset, SynVid
+- [ ] Training
+
+
+## 🔧 Installation
+The code is tested on Python 3.10.0, CUDA 11.8 and A100.
+```
+conda create -n accvideo python==3.10.0
+conda activate accvideo
+
+pip install torch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 --index-url https://download.pytorch.org/whl/cu118
+pip install -r requirements.txt
+pip install flash-attn==2.7.3 --no-build-isolation
+pip install "huggingface_hub[cli]"
+```
+
+## 🤗 Checkpoints
+To download the checkpoints, use the following command:
+```bash
+# Download the model weight
+huggingface-cli download aejion/AccVideo --local-dir ./ckpts
+```
+
+## 🚀 Inference
+We recommend using a GPU with 80GB of memory. To run the inference, use the following command:
+```bash
+export MODEL_BASE=./ckpts
+python sample_t2v.py \
+    --height 544 \
+    --width 960 \
+    --num_frames 93 \
+    --num_inference_steps 50 \
+    --guidance_scale 1 \
+    --embedded_cfg_scale 6 \
+    --flow_shift 7 \
+    --flow-reverse \
+    --prompt_file ./assets/prompt.txt \
+    --seed 1024 \
+    --output_path ./results/accvideo-544p \
+    --model_path ./ckpts \
+    --dit-weight ./ckpts/accvideo-t2v-5-steps/diffusion_pytorch_model.pt
+```
+
+The following table shows the comparisons on inference time using a single A100 GPU:
+
+|    Model     | Setting(height/width/frame) | Inference Time(s) |
+|:------------:|:---------------------------:|:-----------------:|
+| HunyuanVideo |       720px1280px129f       |       3234        |
+|     Ours     |       720px1280px129f       | 380(8.5x faster)  |
+| HunyuanVideo |        544px960px93f        |        704        |
+|     Ours     |        544px960px93f        |  91(7.7x faster)  |
+
+
+## 🔗 BibTeX
+
+If you find [AccVideo]() useful for your research and applications, please cite using this BibTeX:
+
+```BibTeX
+
+```
+
+## Acknowledgements
+The code is built upon [FastVideo](https://github.com/hao-ai-lab/FastVideo) and [HunyuanVideo](https://github.com/Tencent/HunyuanVideo), we thank all the contributors for open-sourcing.