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---
license: apache-2.0
task_categories:
- text-to-video
language:
- en
tags:
- data-juicer
- multimodal
- text-to-video
---
# <span style="font-family: 'Courier New', monospace; font-weight: bold">Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development
## Project description
The emergence of large-scale multi-modal generative models has drastically advanced artificial intelligence, introducing unprecedented levels of performance and functionality.
However, optimizing these models remains challenging due to historically isolated paths of model-centric and data-centric developments, leading to suboptimal outcomes and inefficient resource utilization.
In response, we present a novel sandbox suite tailored for integrated data-model co-development. This sandbox provides a comprehensive experimental platform, enabling rapid iteration and insight-driven refinement of both data and models.
Our proposed "Probe-Analyze-Refine" workflow, validated through applications on [T2V-Turbo](https://github.com/Ji4chenLi/t2v-turbo) and achieve a new state-of-the-art on [VBench leaderboard](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard) with 1.09% improvement from T2V-Turbo. Our experiment code and model are released at [Data-Juicer Sandbox](https://github.com/modelscope/data-juicer/blob/main/docs/Sandbox.md).
## Dataset Information
- The whole dataset is available [here](http://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/MM_data/our_refined_data/Data-Juicer-T2V/data_juicer_t2v_optimal_data_pool.zip) (About 227.5GB).
- Number of samples: 147,176 (Include videos and keep ~12.09% from the original dataset)
- The original dataset totals 1,217k instances from [InternVid](https://github.com/OpenGVLab/InternVideo/tree/main/Data/InternVid) (606k), [Panda-70M](https://github.com/snap-research/Panda-70M) (605k), and [MSR-VTT](https://www.microsoft.com/en-us/research/publication/msr-vtt-a-large-video-description-dataset-for-bridging-video-and-language/) (6k).
## Refining Recipe
```yaml
# global parameters
# global parameters
project_name: 'Data-Juicer-recipes-T2V-optimal'
dataset_path: '/path/to/your/dataset' # path to your dataset directory or file
export_path: '/path/to/your/dataset.jsonl'
np: 4 # number of subprocess to process your dataset
# process schedule
# a list of several process operators with their arguments
process:
- video_nsfw_filter:
hf_nsfw_model: Falconsai/nsfw_image_detection
score_threshold: 0.000195383
frame_sampling_method: uniform
frame_num: 3
reduce_mode: avg
any_or_all: any
mem_required: '1GB'
- video_frames_text_similarity_filter:
hf_clip: openai/clip-vit-base-patch32
min_score: 0.306337
max_score: 1.0
frame_sampling_method: uniform
frame_num: 3
horizontal_flip: false
vertical_flip: false
reduce_mode: avg
any_or_all: any
mem_required: '10GB'
``` |