LLaMA-VID empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token.
Model type: LLaMA-VID is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. LLaMA-VID empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token. We build this repo based on LLaVA.
Model date: llama-vid-7b-pretrain-224 was trained on 10/2023.
Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.
Where to send questions or comments about the model: https://github.com/dvlab-research/LLaMA-VID/issues
Primary intended uses: The primary use of LLaMA-VID is research on large multimodal models and chatbots.
Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
This model is trained based on LLaVA-1.5 dataset, including
LLaMA-VID empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token.
Model type: LLaMA-VID is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. LLaMA-VID empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token. We build this repo based on LLaVA.
Model date: llama-vid-7b-pretrain-224 was trained on 10/2023.
Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.
Where to send questions or comments about the model: https://github.com/dvlab-research/LLaMA-VID/issues
Primary intended uses: The primary use of LLaMA-VID is research on large multimodal models and chatbots.
Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
This model is trained based on LLaVA-1.5 dataset, including