Edit model card

πŸŽ₯ CogVideoX-2B-Img2Vid πŸš€

Fine-tuned on 10 million videos for high-quality generation at SBS levels comparable to CogVideoX-5B! 🌟

Model Highlights 🌟

  • Fine-tuned on 10 million videos for exceptional image-to-video generation quality.

  • Performance benchmarked to match SBS standards at CogVideoX-5B i2v level.

Usage Examples πŸ”₯

Try it for free on nim.video

CLI Inference 🌐

python -m inference.cli_demo \
    --video_path "resources/truck.jpg" \
    --prompt "A truck is driving through a dirt road, showcasing its capability for off-roading." \
    --model_path NimVideo/cogvideox-2b-img2vid

Gradio Inference with Web Demo πŸ–₯️

python -m inference.gradio_web_demo \
    --model_path NimVideo/cogvideox-2b-img2vid

ComfyUI Example πŸ’‘

Workflow Preview

πŸ”— JSON Workflow Example

πŸ”§ Find the custom ComfyUI node here.

Quick Start πŸš€

1️⃣ Clone the Repository

git clone https://github.com/Nim-Video/cogvideox-2b-img2vid.git
cd cogvideox-2b-img2vid

2️⃣ Set up a Virtual Environment

python -m venv venv
source venv/bin/activate

3️⃣ Install Requirements

pip install -r requirements.txt

Acknowledgements πŸ™

This project builds on the foundational work of CogVideoX.

Downloads last month
1,228
Inference API
Inference API (serverless) does not yet support diffusers models for this pipeline type.

Space using NimVideo/cogvideox-2b-img2vid 1