the_cauldron
VerifiedCollection of 50 vision-language training sets for multimodal fine-tuning.
What is the_cauldron?
The Cauldron is a single Hugging Face dataset that bundles training portions of fifty public vision-language collections released alongside Idefics2.
It supports researchers building or adapting vision-language models that require large-scale image-text training data.
Data preview
A real sample from the dataset — 2 columns.
| imagesList | textsList |
|---|---|
| [{"src":"https://datasets-server.huggingface.co/cached-assets/HuggingFaceM4/the_cauldron/--/847a98a779b1652d65111daf20c972dfcd333605/--/ai2d/train/0/images/image-1d100e9.jpg?Expires=1781513188&Signatu | [{"user":"Question: What do respiration and combustion give out\nChoices:\nA. Oxygen\nB. Carbon dioxide\nC. Nitrogen\nD. Heat\nAnswer with the letter.","assistant":"Answer: B","source":"AI2D"}] |
| [{"src":"https://datasets-server.huggingface.co/cached-assets/HuggingFaceM4/the_cauldron/--/847a98a779b1652d65111daf20c972dfcd333605/--/ai2d/train/1/images/image-1d100e9.jpg?Expires=1781513188&Signatu | [{"user":"Question: From the given food web, name any two herbivores?\nChoices:\nA. coyote, bobcat\nB. dingo, jack rabbit\nC. dingo, bobcat\nD. roadrunner&jack rabbit\nAnswer with the letter.","assist |
| [{"src":"https://datasets-server.huggingface.co/cached-assets/HuggingFaceM4/the_cauldron/--/847a98a779b1652d65111daf20c972dfcd333605/--/ai2d/train/2/images/image-1d100e9.jpg?Expires=1781513188&Signatu | [{"user":"Question: Anatomy One of a series of long curved bones occurring in 12 pairs in humans is called.\nChoices:\nA. diaphram\nB. lung\nC. none\nD. ribs\nAnswer with the letter.","assistant":"Ans |
| [{"src":"https://datasets-server.huggingface.co/cached-assets/HuggingFaceM4/the_cauldron/--/847a98a779b1652d65111daf20c972dfcd333605/--/ai2d/train/3/images/image-1d100e9.jpg?Expires=1781513188&Signatu | [{"user":"Question: What process does this diagram portray?\nChoices:\nA. Erosion\nB. Water Cycle\nC. Photosynthesis\nD. Moon Phases\nAnswer with the letter.","assistant":"Answer: C","source":"AI2D"}, |
| [{"src":"https://datasets-server.huggingface.co/cached-assets/HuggingFaceM4/the_cauldron/--/847a98a779b1652d65111daf20c972dfcd333605/--/ai2d/train/4/images/image-1d100e9.jpg?Expires=1781513188&Signatu | [{"user":"Question: If the Termites in the community below were destroyed, which population would be most directly affected?\nChoices:\nA. Dingoes\nB. Mice\nC. Northern brown bandicoot\nD. none of abo |
Dataset structure
| Subset | Split | Rows |
|---|---|---|
| ai2d | train | 2,434 |
| aokvqa | train | 16,539 |
| chart2text | train | 26,961 |
| chartqa | train | 18,265 |
| clevr | train | 70,000 |
| clevr_math | train | 70,000 |
| cocoqa | train | 46,287 |
| datikz | train | 47,974 |
| diagram_image_to_text | train | 300 |
| docvqa | train | 10,189 |
| dvqa | train | 200,000 |
| figureqa | train | 100,000 |
What you can build with the_cauldron
Fine-tune vision-language models
Train or adapt models like Idefics2 on a large aggregated set of image-text pairs for improved multimodal understanding.
Benchmark data mixing strategies
Experiment with sampling from 50 source datasets to study effects of data diversity on model performance.
Build instruction-tuned VL systems
Use the combined training splits to create datasets for visual question answering or captioning pipelines.
Load the_cauldron
from datasets import load_dataset
ds = load_dataset("HuggingFaceM4/the_cauldron")- 1pip install datasets
- 2from datasets import load_dataset
- 3dataset = load_dataset('HuggingFaceM4/the_cauldron')
- 4Access splits via dataset['train'] and inspect image/text columns
- 5Filter or subsample examples as needed for your training loop
the_cauldron: pros & cons
Pros
- +Aggregates 50 vision-language sources into one collection
- +Scale of 1-10 million examples suitable for fine-tuning
- +Directly prepared for Idefics2-style training
- +Accessible through standard Hugging Face datasets API
Cons
- –License terms inherited from 50 original datasets may conflict
- –Potential duplicates or inconsistent formatting across sources
- –No validation or test splits provided
Frequently asked questions
A collection of training splits from 50 vision-language datasets compiled by Hugging Face M4, containing between one and ten million examples.
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