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  - diffusers
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  ---
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- # cogvideox-2b-img2vid
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- You can try it for free on nim.video!!
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63fde49f6315a264aba6a7ed/8vOYgS-Wm51BgOKv4Jnpp.mp4"></video>
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- ### ComfyUI Example
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- <p>
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- <img src="cogvideox-2b-img2vid-workflow.png" width="800" height="400" title="preview"/>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  </p>
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- <p>
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- <a href="cogvideox-2b-img2vid-workflow.json">JSON Workflow Example</a>
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  </p>
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- ComfyUI custom node can be found <a href="https://github.com/Nim-Video/ComfyUI-CogVideoXWrapper">here</a>.
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- ### How to
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- Clone repo
 
 
 
 
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  ```bash
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  git clone https://github.com/Nim-Video/cogvideox-2b-img2vid.git
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  cd cogvideox-2b-img2vid
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  ```
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-
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- Create venv
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  ```bash
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  python -m venv venv
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  source venv/bin/activate
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  ```
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-
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- Install requirements
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  ```bash
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  pip install -r requirements.txt
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  ```
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-
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- ### Simple examples
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- #### Inference with cli
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- ```bash
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- python -m inference.cli_demo \
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- --video_path "resources/truck.jpg" \
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- --prompt "A truck is driving through a dirt road, showcasing its capability for off-roading." \
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- --model_path NimVideo/cogvideox-2b-img2vid
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- ```
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- #### Inference with Gradio
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- ```bash
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- python -m inference.gradio_web_demo \
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- --model_path NimVideo/cogvideox-2b-img2vid
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- ```
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- ## Acknowledgements
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- Original code and models [CogVideoX](https://github.com/THUDM/CogVideo/tree/main).
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+ # πŸŽ₯ CogVideoX-2B-Img2Vid πŸš€
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+ ### Fine-tuned on 10 million videos for high-quality generation at SBS levels comparable to CogVideoX-5B! 🌟
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+
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+ # Model Highlights 🌟
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+ - Fine-tuned on 10 million videos for exceptional image-to-video generation quality.
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+ - Performance benchmarked to match SBS standards at CogVideoX-5B i2v level.
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+
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+
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+ ## Usage Examples πŸ”₯
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+
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+ ### Try it for free on [nim.video](https://nim.video)
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  <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63fde49f6315a264aba6a7ed/8vOYgS-Wm51BgOKv4Jnpp.mp4"></video>
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+ ### CLI Inference 🌐
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+ ```bash
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+ python -m inference.cli_demo \
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+ --video_path "resources/truck.jpg" \
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+ --prompt "A truck is driving through a dirt road, showcasing its capability for off-roading." \
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+ --model_path NimVideo/cogvideox-2b-img2vid
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+
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+ ```
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+ ## Gradio Inference with Web Demo πŸ–₯️
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+ ```bash
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+ python -m inference.gradio_web_demo \
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+ --model_path NimVideo/cogvideox-2b-img2vid
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+ ```
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+ ### ComfyUI Example πŸ’‘
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+
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+ <p align="center">
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+ <img src="cogvideox-2b-img2vid-workflow.png" width="800" height="400" alt="Workflow Preview" title="Workflow Example Preview"/>
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  </p>
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+ <p align="center">
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+ <a href="cogvideox-2b-img2vid-workflow.json">πŸ”— JSON Workflow Example</a>
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  </p>
 
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+
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+ ### πŸ”§ [Find the custom ComfyUI node here.](https://github.com/Nim-Video/ComfyUI-CogVideoXWrapper)
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+
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+ ## Quick Start πŸš€
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+
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+ 1️⃣ Clone the Repository
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  ```bash
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  git clone https://github.com/Nim-Video/cogvideox-2b-img2vid.git
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  cd cogvideox-2b-img2vid
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  ```
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+ 2️⃣ Set up a Virtual Environment
 
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  ```bash
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  python -m venv venv
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  source venv/bin/activate
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  ```
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+ 3️⃣ Install Requirements
 
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  ```bash
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  pip install -r requirements.txt
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  ```
 
 
 
 
 
 
 
 
 
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+ ## Acknowledgements πŸ™
 
 
 
 
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+ This project builds on the foundational work of [CogVideoX](https://github.com/THUDM/CogVideo/tree/main).
 
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