metadata

dataset_info:
  features:
    - name: conversations
      list:
        - name: from
          dtype: string
        - name: value
          dtype: string
    - name: image
      dtype: string
  splits:
    - name: train
      num_bytes: 139133435
      num_examples: 595375
  download_size: 39144914
  dataset_size: 139133435
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: other
task_categories:
  - visual-question-answering
  - question-answering
language:
  - hi
  - en
tags:
  - VLM
pretty_name: hindi-vqa
size_categories:
  - 100K<n<1M

LLaVA Visual Instruct CC3M 595K Pretrain Dataset Card

Dataset details

Dataset type: LLaVA Visual Instruct CC3M Pretrain 595K is a subset of CC-3M dataset, filtered with a more balanced concept coverage distribution. Captions are also associated with BLIP synthetic caption for reference. It is constructed for the pretraining stage for feature alignment in visual instruction tuning. We aim to build large multimodal towards GPT-4 vision/language capability.

Dataset date: LLaVA Visual Instruct CC3M Pretrain 595K was created in April 2023.

Dataset structure:

chat.json contains the multimodal synthesized conversation from the image-caption pairs, by adding randomly selected instructions like: "Describe this image". It is used for pretraining in LLaVA. We use the raw CC-3M caption as the default answer.
metadata.json contains the meta data of the image index in CC-3M, image file name, image URL, original CC-3M caption, synthetic BLIP caption. Note that ~10% of the samples are not associated with BLIP caption yet in this release.
images.zip Can be found from here images
Bilingual This dataset contains both hindi and english captions

License: Must comply with license of CC-3M, BLIP (if you use their synthetic caption).

CC-3M The dataset may be freely used for any purpose, although acknowledgement of Google LLC ("Google") as the data source would be appreciated. The dataset is provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Intended use

Primary intended uses: The primary use of LLaVA 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.