---
license: cc-by-nc-4.0
task_categories:
- visual-question-answering
- question-answering
language:
- en
pretty_name: ShareGPT4V Captions 1.2M Dataset Card
size_categories:
- 1M<n
configs:
- config_name: ShareGPT4V
  data_files: sharegpt4v_instruct_gpt4-vision_cap100k.json
- config_name: ShareGPT4V-PT
  data_files: share-captioner_coco_lcs_sam_1246k_1107.json
---

# News

**[2024/5/8]** We released **[ShareGPT4Video](https://sharegpt4video.github.io/)**, a large-scale video-caption dataset, with **40K** captions annotated by GPT4V and **4.8M** captions annotated by our ShareCaptioner-Video. The total videos last with **300** hours and **3000** hours separately!

# ShareGPT4V 1.2M Dataset Card

## Dataset details

**Dataset type:**
ShareGPT4V Captions 1.2M is a set of GPT4-Vision-powered multi-modal captions data.

It is constructed to enhance modality alignment and fine-grained visual concept perception in Large Multi-Modal Models (LMMs) during both the pre-training and supervised fine-tuning stages. This advancement aims to bring LMMs towards GPT4-Vision capabilities.

* sharegpt4v_instruct_gpt4-vision_cap100k.json is generated by GPT4-Vision (ShareGPT4V).
* share-captioner_coco_lcs_sam_1246k_1107.json is generated by our Share-Captioner trained on GPT4-Vision-generated data (ShareGPT4V-PT).
* sharegpt4v_mix665k_cap23k_coco-ap9k_lcs3k_sam9k_div2k.json is curated from sharegpt4v_instruct_gpt4-vision_cap100k.json for the supervised fine-tuning stage.

**Dataset date:**
ShareGPT4V Captions 1.2M was collected in 11.07 2023.

**Paper or resources for more information:**
[[Project](https://ShareGPT4V.github.io/)] [[Paper](https://huggingface.co/papers/2311.12793)] [[Code](https://github.com/ShareGPT4Omni/ShareGPT4V)]

**License:**
Attribution-NonCommercial 4.0 International
It should abide by the policy of OpenAI: https://openai.com/policies/terms-of-use

## Intended use
**Primary intended uses:**
The primary use of ShareGPT4V Captions 1.2M is research on large multimodal models and chatbots.

**Primary intended users:**
The primary intended users of this dataset are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
