merve's picture
merve HF staff
Add new task tag
aa9e3bd verified
|
raw
history blame
2.69 kB
metadata
license: mit
library_name: peft
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
  - chenjoya/videollm-online-chat-ego4d-134k
language:
  - en
tags:
  - llama
  - llama-3
  - multimodal
  - llm
  - video stream
  - online video understanding
  - video understanding
pipeline_tag: video-text-to-text

Model Card for Model ID

https://showlab.github.io/videollm-online/

Model Details

  • LLM: meta-llama/Meta-Llama-3-8B-Instruct
  • Vision Strategy:
    • Frame Encoder: google/siglip-large-patch16-384
    • Frame Tokens: CLS Token + Avg Pooled 3x3 Tokens
    • Frame FPS: 2 for training, 2~10 for inference
    • Frame Resolution: max resolution 384, with zero-padding to keep aspect ratio
    • Video Length: 10 minutes
  • Training Data: Ego4D Narration Stream 113K + Ego4D GoalStep Stream 21K

Model Sources

Uses

  • First, clone the github repository and follow the installation instruction:
git clone https://github.com/showlab/videollm-online

Ensure you have Miniconda and Python version >= 3.10 installed, then run:

conda install -y pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
pip install transformers accelerate deepspeed peft editdistance Levenshtein tensorboard gradio moviepy submitit
pip install flash-attn --no-build-isolation

PyTorch source will make ffmpeg installed, but it is an old version and usually make very low quality preprocessing. Please install newest ffmpeg following:

wget https://johnvansickle.com/ffmpeg/releases/ffmpeg-release-amd64-static.tar.xz
tar xvf ffmpeg-release-amd64-static.tar.xz
rm ffmpeg-release-amd64-static.tar.xz
mv ffmpeg-7.0.1-amd64-static ffmpeg

If you want to try our model with the audio in real-time streaming, please also clone ChatTTS.

pip install omegaconf vocos vector_quantize_pytorch cython
git clone git+https://github.com/2noise/ChatTTS
mv ChatTTS demo/rendering/
  • Launch the gradio demo locally with:
python -m demo.app --resume_from_checkpoint chenjoya/videollm-online-8b-v1plus
  • Or launch the CLI locally with:
python -m demo.cli --resume_from_checkpoint chenjoya/videollm-online-8b-v1plus

Citation

@inproceedings{videollm-online,
  author       = {Joya Chen and Zhaoyang Lv and Shiwei Wu and Kevin Qinghong Lin and Chenan Song and Difei Gao and Jia-Wei Liu and Ziteng Gao and Dongxing Mao and Mike Zheng Shou},
  title        = {VideoLLM-online: Online Video Large Language Model for Streaming Video},
  booktitle    = {CVPR},
  year         = {2024},
}