Unleash the Power of Video-LLaMA: Revolutionizing Language Models with Video and Audio Understanding!
Tags: yogyaopensource, ai, midjourney, llama
Published: 2023-06-12 11:51:42

Prepare to be blown away by the cutting-edge [Video-LLaMA](https://github.com/DAMO-NLP-SG/Video-LLaMA) project! We're pushing the boundaries of language models by equipping them with the remarkable ability to comprehend video and audio. Get ready for an extraordinary adventure! 🌟

## 🌟 Video-LLaMA Overview:

Discover the secrets behind the mind-boggling capabilities of Video-LLaMA. Built on the foundations of [BLIP-2](https://huggingface.co/docs/transformers/main/model_doc/blip-2) and [MiniGPT-4](https://huggingface.co/Vision-CAIR/MiniGPT-4), Video-LLaMA consists of two extraordinary components:

1️⃣ VL Branch: 
Combining [ViT-G/14](https://huggingface.co/laion/CLIP-ViT-g-14-laion2B-s12B-b42K) and BLIP-2 Q-Former, this branch is a visual encoding powerhouse. Trained on the vast [Webvid-2M](https://paperswithcode.com/dataset/webvid) video caption dataset, it excels in generating accurate text descriptions of videos. To enhance its understanding of static visual concepts, we've incorporated image-text pairs from [LLaVA](https://github.com/haotian-liu/LLaVA).

2️⃣ AL Branch: 
The audio encoding marvel! Leveraging the extraordinary [ImageBind](https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/)-Huge, this branch specializes in audio comprehension. Trained exclusively on video/image instrucaption data, it seamlessly connects the output of ImageBind to the language decoder. During cross-modal training, only the Video/Audio Q-Former, positional embedding layers, and linear layers are trainable, ensuring maximum efficiency and effectiveness.

## 🌈 Astonishing Example Outputs:
Prepare to be dazzled by the astonishing outputs of Video-LLaMA:

- Experience videos with immersive background sound, transporting you to the heart of the action! 🎬
- Delve into soundless videos that convey rich visual information with incredible clarity. 🎥
- Behold stunning static images that captivate your imagination and tell unforgettable stories. 🖼️

## 🔑 Pre-trained & Fine-tuned Checkpoints:
Unlock the full potential of Video-LLaMA with our meticulously crafted checkpoints. These checkpoints store the learnable parameters, including positional embedding layers, Video/Audio Q-Former, and linear projection layers. Use the provided links to access these invaluable resources and embark on your journey to video and audio understanding.

## 💻 How to Harness the Power:
Unleashing the extraordinary capabilities of Video-LLaMA is a breeze:
1️⃣ Environment Preparation: Install ffmpeg and create a conda environment following the provided instructions to ensure a seamless experience.
2️⃣ Prerequisites: Make sure you have obtained the essential pre-trained language decoder, visual encoder, and audio encoder checkpoints, as detailed in the repository.
3️⃣ Download Learnable Weights: Utilize git-lfs to effortlessly download the learnable weights of Video-LLaMA. The repository contains the model weights of all the variants. Alternatively, you can choose to download the weights on demand, based on your specific requirements.
4️⃣ Run Demo Locally: Customize the configuration files to suit your needs and execute the provided script to run the mesmerizing Video-LLaMA demo on your local machine.

## 🎓 Training:
Unlock the secrets of Video-LLaMA through comprehensive training:
1️⃣ Pre-training: Dive into data preparation, download the required datasets, and run the pre-training script using Webvid-2.5M and LLaVA-CC3M datasets. Lay the groundwork for exceptional understanding.
2️⃣ Instruction Fine-tuning: Prepare for the next level! Utilize image-based instructions from LLaVA, image-based instructions from MiniGPT-4, and video-based instructions from VideoChat to fine-tune your Video-LLaMA model. Experience unparalleled precision and accuracy.

## 🙏 Acknowledgement:
We extend our deepest gratitude to the extraordinary projects that have influenced and contributed to the development of Video-LLaMA. We're indebted to MiniGPT-4, [FastChat](https://github.com/lm-sys/FastChat), BLIP-2, [EVA-CLIP](https://huggingface.co/QuanSun/EVA-CLIP), ImageBind, LLaMA, VideoChat, LLaVA, WebVid, and [mPLUG-Owl](https://github.com/X-PLUG/mPLUG-Owl) for their invaluable contributions. Special thanks to Midjourney for creating the stunning Video-LLaMA logo, encapsulating the essence of our groundbreaking project.

Join us on this remarkable journey and unlock the infinite possibilities of Video-LLaMA in the realm of video understanding! Prepare to be amazed like never before. Together, we'll redefine the boundaries of language models and revolutionize the way we comprehend videos. Let's embark on this incredible adventure today!

## 🔗 Explore the Video-LLaMA Demo:
Discover the extraordinary capabilities of Video-LLaMA by visiting our Hugging Face demo at: [Video-LLaMA Demo](https://huggingface.co/spaces/DAMO-NLP-SG/Video-LLaMA)