Duplicate from chetwinlow1/Ovi

Co-authored-by: Low Qi Hong Chetwin <chetwinlow1@users.noreply.huggingface.co>

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README.md

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+---
+language:
+- en
+license: apache-2.0
+pipeline_tag: image-to-video
+library_name: ovi
+base_model:
+- Wan-AI/Wan2.2-TI2V-5B
+---
+
+<div align="center">
+<h1> Ovi: Twin Backbone Cross-Modal Fusion for Audio-Video Generation </h1>
+
+<a href="https://arxiv.org/abs/2510.01284"><img src="https://img.shields.io/badge/arXiv%20paper-2510.01284-b31b1b.svg"></a>
+<a href="https://aaxwaz.github.io/Ovi/"><img src="https://img.shields.io/badge/Project_page-More_visualizations-green"></a>
+<a href="https://huggingface.co/chetwinlow1/Ovi"><img src="https://img.shields.io/static/v1?label=%F0%9F%A4%97%20Hugging%20Face&message=Model&color=orange"></a>
+
+[Chetwin Low](https://www.linkedin.com/in/chetwin-low-061975193/)<sup> * 1 </sup>, [Weimin Wang](https://www.linkedin.com/in/weimin-wang-will/)<sup> * &dagger; 1 </sup>, [Calder Katyal](https://www.linkedin.com/in/calder-katyal-a8a9b3225/)<sup> 2 </sup><br>
+<sup> * </sup>Equal contribution, <sup> &dagger; </sup>Project Lead<br>
+<sup> 1 </sup>Character AI, <sup> 2 </sup>Yale University
+</div>
+
+---
+
+## 🎥 Video Demo
+
+### 🆕 Ovi 1.1 10-Second Demo
+<div align="center">
+  <video src="https://github.com/user-attachments/assets/191f51fb-ef5a-4197-b26f-a5369dc2c007"
+         width="70%" controls playsinline preload="metadata"></video>
+  <p><em>Ovi 1.1 – 10-second temporally consistent video generation (960 × 960 resolution)</em></p>
+</div>
+
+### 🎬 Original 5-Second Demo
+<div align="center">
+  <video src="https://github.com/user-attachments/assets/351bd707-8637-4412-ab53-5e85935309e3" width="70%" poster=""> </video>
+</div>
+
+---
+
+# 🆕 Ovi 1.1 Update (10 November 2025)
+- **Key Feature:** Enables *temporal-consistent 10-second video generation* at **960 × 960 resolution**  
+- **Training Improvements:**  
+  - Trained natively on 960×960 resolution videos  
+  - Dataset includes **100% more videos** for greater diversity
+  - 
+- **Prompt Format Update:**  
+  - Audio descriptions should now be written as  
+    ```
+    Audio: ...
+    ```  
+    instead of using  
+    ```
+    <AUDCAP> ... <ENDAUDCAP>
+    ```
+
+## 🌟 Key Features
+Ovi is a veo-3-like, **video + audio generation model** that simultaneously generates both video and audio content from text or text + image inputs.
+- **🎬 Video+Audio Generation**: Generate synchronized video and audio content simultaneously
+  - **🎵 High-Quality Audio Branch**: We designed and pretrained our 5B audio branch from scratch using our high quality in-house audio datasets
+- **📝 Flexible Input**: Supports text-only or text+image conditioning
+- **⏱️ 10-second (or 5-second) Videos**: Generates 10-second or 5-second videos at 24 FPS, resolution of 960x960p, at various aspect ratios (9:16, 16:9, 1:1, etc)
+- **🔧 ComfyUI Integration**: ComfyUI support is now available via [ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper), related [PR](https://github.com/kijai/ComfyUI-WanVideoWrapper/issues/1343#issuecomment-3382969479).
+- **🎬 Create videos now on wavespeed.ai**: https://wavespeed.ai/models/character-ai/ovi/image-to-video & https://wavespeed.ai/models/character-ai/ovi/text-to-video
+- **🎬 Create videos now on HuggingFace**: https://huggingface.co/spaces/akhaliq/Ovi
+
+### 🎯 10-second examples
+
+<div align="center"><table><tr>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/c7e75ef8-adf9-4612-a279-56e4cf7ce146" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/025f5936-883e-4851-bf35-1a809769ba97" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/9e5bf0df-74d6-4e04-a7d0-e5b64616afa9" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/499cefde-c5f8-4afc-b77a-6cd9293b8ac6" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/73390370-afa7-4604-97b6-80995b615d43" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/e11c6f2d-6098-41bb-9bca-a99796a58424" width="100%" controls playsinline preload="metadata"></video>
+</td>
+</tr></table>
+<p>Click the ⛶ button on any video to view full screen.</p>
+</div>
+
+### 🎯 5-second examples
+
+<div align="center"><table><tr>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/c6b35565-df00-4494-b38a-7dcae90f63e5" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/2ce6ff72-eadd-4cf4-b343-b465f0624571" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/7c1dbbea-dfb7-44d7-a4a1-d70a2e00f51a" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/4e41d1b3-7d39-49a8-ab71-e910088f29ee" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/4ad3ad70-1fea-4a2d-9201-808f4746c55e" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/60792c08-12de-49c3-860f-12ac94730940" width="100%" controls playsinline preload="metadata"></video>
+</td>
+<td width="20%">
+<video src="https://github.com/user-attachments/assets/0f3a318b-ac74-43c4-81a5-503f06c65e99" width="100%" controls playsinline preload="metadata"></video>
+</td>
+</tr></table>
+<p>Click the ⛶ button on any video to view full screen.</p>
+</div>
+
+
+---
+## 📋 Todo List
+
+- [x] Release research paper and [website for demos](https://aaxwaz.github.io/Ovi)
+- [x] Checkpoint of 11B model
+- [x] Inference Codes
+  - [x] Text or Text+Image as input
+  - [x] Gradio application code
+  - [x] Multi-GPU inference with or without the support of sequence parallel
+  - [x] fp8 weights and improved memory efficiency (credits to [@rkfg](https://github.com/rkfg))
+  - [x] qint8 quantization thanks to [@gluttony-10](https://github.com/character-ai/Ovi/commits?author=gluttony-10)
+  - [ ] Improve efficiency of Sequence Parallel implementation
+  - [ ] Implement Sharded inference with FSDP
+- [x] Video creation example prompts and format
+- [x] Finetune model with higher resolution data, and RL for performance improvement. 
+- [x] Longer video generation (10s)
+- [ ] Reference voice condition
+- [ ] Distilled model for faster inference
+- [ ] Training scripts
+
+---
+
+## 🎨 An Easy Way to Create
+
+We provide example prompts to help you get started with Ovi:
+- **Text-to-Audio-Video (T2AV) 10s**: [`example_prompts/gpt_examples_t2v.csv`](example_prompts/gpt_examples_10s_t2v.csv)
+- **Image-to-Audio-Video (I2AV) 10s**: [`example_prompts/gpt_examples_i2v.csv`](example_prompts/gpt_examples_10s_i2v.csv)
+- **Text-to-Audio-Video (T2AV)**: [`example_prompts/gpt_examples_t2v.csv`](example_prompts/gpt_examples_t2v.csv)
+- **Image-to-Audio-Video (I2AV)**: [`example_prompts/gpt_examples_i2v.csv`](example_prompts/gpt_examples_i2v.csv)
+
+### 📝 Prompt Format
+
+Our prompts use special tags to control speech and audio:
+- **Speech**: `<S>Your speech content here<E>` - Text enclosed in these tags will be converted to speech
+- **Audio Description**: `Audio: YOUR AUDIO DESCRIPTION` - Describes the audio or sound effects present in the video **at the end of prompt!**
+
+---
+
+
+## 📦 Installation
+
+### Step-by-Step Installation
+
+```bash
+# Clone the repository
+git clone https://github.com/character-ai/Ovi.git
+
+cd Ovi
+
+# Create and activate virtual environment
+virtualenv ovi-env
+source ovi-env/bin/activate
+
+# Install PyTorch first
+pip install torch==2.6.0 torchvision torchaudio
+
+# Install other dependencies
+pip install -r requirements.txt
+
+# Install Flash Attention
+pip install flash_attn --no-build-isolation
+```
+
+### Alternative Flash Attention Installation (Optional)
+If the above flash_attn installation fails, you can try the Flash Attention 3 method:
+```bash
+git clone https://github.com/Dao-AILab/flash-attention.git
+cd flash-attention/hopper
+python setup.py install
+cd ../..  # Return to Ovi directory
+```
+
+## Download Weights
+To download our main Ovi checkpoint, as well as T5 and vae decoder from Wan, and audio vae from MMAudio
+
+```
+# Default is downloaded to ./ckpts, and the inference yaml is set to ./ckpts so no change required
+# Default installs all versions of Ovi models, 720x720_5s, 960x960_5s, 960x960_10s
+python3 download_weights.py
+# For qint8 also ues python3 download_weights.py
+
+OR
+
+# Optional can specific --output-dir to download to a specific directory
+# but if a custom directory is used, the inference yaml has to be updated with the custom directory
+python3 download_weights.py --output-dir <custom_dir>
+
+# Optional can specific --models to download selective versions of Ovi instead of all of them
+# but if a custom directory is used, the inference yaml has to be updated with the custom directory
+python3 download_weights.py --models 960x960_10s # ["720x720_5s", "960x960_5s", "960x960_10s"]
+
+# Additionally, if you only have ~ 24Gb of GPU vram, please download the fp8 quantized version of the model, and follow the following instructions in sections below to run with fp8
+wget -O "./ckpts/Ovi/model_fp8_e4m3fn.safetensors" "https://huggingface.co/rkfg/Ovi-fp8_quantized/resolve/main/model_fp8_e4m3fn.safetensors"
+```
+
+## 🚀 Run Examples
+
+### ⚙️ Configure Ovi
+
+Ovi's behavior and output can be customized by modifying [ovi/configs/inference/inference_fusion.yaml](ovi/configs/inference/inference_fusion.yaml) configuration file.
+The following parameters control generation quality, video resolution, and how text, image, and audio inputs are balanced:
+
+```yaml
+# Output and Model Configuration
+model_name: "960x960_10s" # ["720x720_5s", "960x960_5s", "960x960_10s"]
+output_dir: "/path/to/save/your/videos"                    # Directory to save generated videos
+ckpt_dir: "/path/to/your/ckpts/dir"                        # Path to model checkpoints
+
+# Generation Quality Settings
+sample_steps: 50                             # Number of denoising steps. Lower (30-40) = faster generation
+solver_name: "unipc"                     # Sampling algorithm for denoising process
+shift: 5.0                               # Timestep shift factor for sampling scheduler
+seed: 100                                # Random seed for reproducible results
+
+# Guidance Strength Control
+audio_guidance_scale: 3.0                # Strength of audio conditioning. Higher = better audio-text sync
+video_guidance_scale: 4.0                # Strength of video conditioning. Higher = better video-text adherence
+slg_layer: 11                            # Layer for applying SLG (Skip Layer Guidance) technique - feel free to try different layers!
+
+# Multi-GPU and Performance
+sp_size: 1                               # Sequence parallelism size. Set equal to number of GPUs used
+cpu_offload: False                       # CPU offload, will largely reduce peak GPU VRAM but increase end to end runtime by ~20 seconds
+fp8: False                               # load fp8 version of model, will have quality degradation and will not have speed up in inference time as it still uses bf16 matmuls, but can be paired with cpu_offload=True, to run model with 24Gb of GPU vram
+
+# Input Configuration
+text_prompt: "/path/to/csv" or "your prompt here"          # Text prompt OR path to CSV/TSV file with prompts
+mode: ['i2v', 't2v', 't2i2v']                          # Generate t2v, i2v or t2i2v; if t2i2v, it will use flux krea to generate starting image and then will follow with i2v
+video_frame_height_width: [704, 1280]    # Video dimensions [height, width] for T2V mode only
+each_example_n_times: 1                  # Number of times to generate each prompt
+
+# Quality Control (Negative Prompts)
+video_negative_prompt: "jitter, bad hands, blur, distortion"  # Artifacts to avoid in video
+audio_negative_prompt: "robotic, muffled, echo, distorted"    # Artifacts to avoid in audio
+```
+
+### 🎬 Running Inference
+
+#### **Single GPU** (Simple Setup)
+```bash
+python3 inference.py --config-file ovi/configs/inference/inference_fusion.yaml
+```
+*Use this for single GPU setups. The `text_prompt` can be a single string or path to a CSV file.*
+
+#### **Multi-GPU** (Parallel Processing)
+```bash
+torchrun --nnodes 1 --nproc_per_node 8 inference.py --config-file ovi/configs/inference/inference_fusion.yaml
+```
+*Use this to run samples in parallel across multiple GPUs for faster processing.*
+
+### Memory & Performance Requirements
+Below are approximate GPU memory requirements for different configurations. Sequence parallel implementation will be optimized in the future.
+All End-to-End time calculated based on a 121 frame, 720x720 video, using 50 denoising steps. Minimum GPU vram requirement to run our model is **32Gb**, fp8 parameters is currently supported, reducing peak VRAM usage to **24Gb** with slight quality degradation.
+
+| Sequence Parallel Size | FlashAttention-3 Enabled | CPU Offload | With Image Gen Model | Peak VRAM Required | End-to-End Time |
+|-------------------------|---------------------------|-------------|-----------------------|---------------|-----------------|
+| 1                       | Yes                        | No          | No                    | ~80 GB        | ~83s         |
+| 1                       | No                        | No          | No                    | ~80 GB        | ~96s         |
+| 1                       | Yes                        | Yes          | No                    | ~80 GB        | ~105s         |
+| 1                       | No                        | Yes          | No                    | ~32 GB        | ~118s         |
+| **1**                       | **Yes**                        | **Yes**          | **Yes**                    | **~32 GB**        | **~140s**         |
+| 4                       | Yes                        | No          | No                    | ~80 GB        | ~55s         |
+| 8                       | Yes                        | No          | No                    | ~80 GB        | ~40s         |
+### Gradio
+We provide a simple script to run our model in a gradio UI. It uses the `ckpt_dir` in `ovi/configs/inference/inference_fusion.yaml` to initialize the model
+```bash
+python3 gradio_app.py
+
+OR
+
+# To enable cpu offload to save GPU VRAM, will slow down end to end inference by ~20 seconds
+python3 gradio_app.py --cpu_offload
+
+OR
+
+# To enable an additional image generation model to generate first frames for I2V, cpu_offload is automatically enabled if image generation model is enabled
+python3 gradio_app.py --use_image_gen
+
+OR
+
+# To run model with 24Gb GPU vram. No need to download additional models.
+python3 gradio_app.py --cpu_offload --qint8
+
+# To run model with 24Gb GPU vram
+python3 gradio_app.py --cpu_offload --fp8
+
+```
+---
+
+## 🙏 Acknowledgements
+
+We would like to thank the following projects:
+
+- **[Wan2.2](https://github.com/Wan-Video/Wan2.2)**: Our video branch is initialized from the Wan2.2 repository
+- **[MMAudio](https://github.com/hkchengrex/MMAudio)**: We reused MMAudio's audio vae. 
+
+---
+
+## 🤝 Collaboration
+
+We welcome all types of collaboration! Whether you have feedback, want to contribute, or have any questions, please feel free to reach out.
+
+**Contact**: [Weimin Wang](https://linkedin.com/in/weimin-wang-will) for any issues or feedback.
+
+
+## ⭐ Citation
+
+If Ovi is helpful, please help to ⭐ the repo.
+
+If you find this project useful for your research, please consider citing our [paper](https://arxiv.org/abs/2510.01284).
+
+
+### BibTeX
+```bibtex
+@misc{low2025ovitwinbackbonecrossmodal,
+      title={Ovi: Twin Backbone Cross-Modal Fusion for Audio-Video Generation}, 
+      author={Chetwin Low and Weimin Wang and Calder Katyal},
+      year={2025},
+      eprint={2510.01284},
+      archivePrefix={arXiv},
+      primaryClass={cs.MM},
+      url={https://arxiv.org/abs/2510.01284}, 
+}
+```

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