csuhan/OneLLM_InstructionTuning
收藏数据集概述
数据格式
所有微调数据被转换为多轮对话格式。.json文件包含一系列训练样本,每个样本包含以下键:id、image和conversations。例如:
json
{id: 000000033471, image: InstructionTuning/image/coco/train2017/000000033471.jpg, conversations: [{from: human, value: What are the colors of the bus in the image?}, {from: gpt, value: The bus in the image is white and red.}, {from: human, value: What feature can be seen on the back of the bus?}, {from: gpt, value: The back of the bus features an advertisement.}]}
下载链接
| 阶段 | 预训练 | 下载链接 | 指令微调 | 下载链接 |
|---|---|---|---|---|
| 模态 | 数据集 | LAION-400M | LLaVA-mix665K | link |
| 图像 | LAION-COCO | link | COCO Caption | link |
| 视频 | WebVid-2.5M | link | MSRVTT Caption | link |
| MSRVTT-QA | link | |||
| Video Conversation | link | |||
| 音频 | WavCaps | link | AudioCaps | link |
| Audio Conversation | link | |||
| 点云 | Cap3D | link | Point Conversation | link |
| 深度图 | CC3M | link | LLaVA-150K | link |
| 法线图 | CC3M | link | LLaVA-150K | link |
| IMU | Ego4D | link | Ego4D | link |
| fMRI | NSD | link | NSD | link |
指令微调数据
注释下载: 请下载注释并将它们放在datasets/InstructionTuning目录下。
然后从上表下载原始数据集,并将它们放在相应的文件夹中。文件结构应如下:
datasets └── InstructionTuning ├── audio │ ├── audioset2 │ ├── audiocap_train.json │ ├── audiocap_val.json │ └── audio_conversation.json ├── depth_normal │ ├── depth │ ├── normal │ ├── llava_instruct_50k_depth.json │ └── llava_instruct_50k_normal.json ├── fmri │ ├── NSD │ └── fmri_fixed_train.json ├── image │ ├── coco │ ├── gqa │ ├── ocr_vqa │ ├── vg │ ├── cococap_train.json │ ├── llava_v1_5_mix665k_image.json │ └── llava_v1_5_mix665k_text.json ├── imu │ ├── ego4d │ └── imu_fixed_50k.json ├── point │ ├── pointllm/8192_npy │ └── pointllm_70k.json └── video ├── msr-vtt/MSR-VTT ├── msrvtt_cap_test.json ├── msrvtt_cap_trainval.json ├── msrvtt_vqa_test.json ├── msrvtt_vqa_train.json ├── msrvtt_vqa_val.json ├── video_complex_reasoning_10k.json ├── video_conversation_10k.json └── video_detail_10k.json



