---
license: apache-2.0
pipeline_tag: image-text-to-text
---
**
TinyLLaVA-Video**
[](https://arxiv.org/abs/2501.15513)[](https://github.com/ZhangXJ199/TinyLLaVA-Video)
For training data, We combine partial data from two datasets: [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-Video-178K) and [
Valley](https://github.com/RupertLuo/Valley).
| Stage | Source | #Sample |
|----------| :---------------------------: | :-----------: |
| Pretrain | LLaVA-Video-178K + Valley | 397k |
| Finetune | LLaVA-Video-178K | 491k |
#### Pretrain Data
We use four subsets of [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-Video-178K): ``0_30_s_academic_v0_1``, ``30_60_s_academic_v0_1``, ``0_30_s_youtube_v0_1``, and ``30_60_s_youtube_v0_1``, supplemented with the filtered [Video-LLaVA](https://huggingface.co/datasets/LanguageBind/Video-LLaVA).
We provide cleaned annotations data, and the video data can be downloaded from [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-Video-178K) and [Video-LLaVA](https://huggingface.co/datasets/LanguageBind/Video-LLaVA).
#### Finetune Data
We use four subsets of [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-Video-178K): ``0_30_s_academic_v0_1``, ``30_60_s_academic_v0_1``, ``0_30_s_youtube_v0_1``, and ``30_60_s_youtube_v0_1``.
We provide cleaned annotations data, and the video data can be downloaded from [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-Video-178K).
#### Organize Data
Organize the image files and annotation files as follows in ``path/to/your/dataset``:
```Shell
dataset
├── academic_source
├── liwei_youtube_videos
├── valley
├── text_files
│ ├── cleaned_video_caption.json
│ ├── cleaned_video_openqa.json
```
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