README.md

---
dataset_info:
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    path: scienceqa(nona_context)/train-*
- config_name: screen2words
  data_files:
  - split: train
    path: screen2words/train-*
- config_name: screenqa
  data_files:
  - split: train
    path: screenqa/train-*
- config_name: sharegpt4o
  data_files:
  - split: train
    path: sharegpt4o/train-*
- config_name: sharegpt4v(coco)
  data_files:
  - split: train
    path: sharegpt4v(coco)/train-*
- config_name: sharegpt4v(knowledge)
  data_files:
  - split: train
    path: sharegpt4v(knowledge)/train-*
- config_name: sharegpt4v(llava)
  data_files:
  - split: train
    path: sharegpt4v(llava)/train-*
- config_name: sharegpt4v(sam)
  data_files:
  - split: train
    path: sharegpt4v(sam)/train-*
- config_name: sketchyvqa
  data_files:
  - split: train
    path: sketchyvqa/train-*
- config_name: slidevqa
  data_files:
  - split: train
    path: slidevqa/train-*
- config_name: spark
  data_files:
  - split: train
    path: spark/train-*
- config_name: spatialsense
  data_files:
  - split: train
    path: spatialsense/train-*
- config_name: spot_the_diff
  data_files:
  - split: train
    path: spot_the_diff/train-*
- config_name: sroie
  data_files:
  - split: train
    path: sroie/train-*
- config_name: st_vqa
  data_files:
  - split: train
    path: st_vqa/train-*
- config_name: sujet_finance
  data_files:
  - split: train
    path: sujet_finance/train-*
- config_name: super_clevr(mathv360k)
  data_files:
  - split: train
    path: super_clevr(mathv360k)/train-*
- config_name: svrd
  data_files:
  - split: train
    path: svrd/train-*
- config_name: synthdog
  data_files:
  - split: train
    path: synthdog/train-*
- config_name: tabmwp
  data_files:
  - split: train
    path: tabmwp/train-*
- config_name: tabmwp(mathv360k)
  data_files:
  - split: train
    path: tabmwp(mathv360k)/train-*
- config_name: tal_ocr_eng
  data_files:
  - split: train
    path: tal_ocr_eng/train-*
- config_name: tallyqa
  data_files:
  - split: train
    path: tallyqa/train-*
- config_name: tat_dqa
  data_files:
  - split: train
    path: tat_dqa/train-*
- config_name: tat_qa
  data_files:
  - split: train
    path: tat_qa/train-*
- config_name: text_OpenMathInstruct-2
  data_files:
  - split: train
    path: text_OpenMathInstruct-2/train-*
- config_name: text_code_feedback
  data_files:
  - split: train
    path: text_code_feedback/train-*
- config_name: text_codefeedback_filtered_instruction
  data_files:
  - split: train
    path: text_codefeedback_filtered_instruction/train-*
- config_name: text_infinitymath
  data_files:
  - split: train
    path: text_infinitymath/train-*
- config_name: text_mathinstruct
  data_files:
  - split: train
    path: text_mathinstruct/train-*
- config_name: text_mathqa
  data_files:
  - split: train
    path: text_mathqa/train-*
- config_name: text_mathstepdpo10k
  data_files:
  - split: train
    path: text_mathstepdpo10k/train-*
- config_name: text_numinamath_cot
  data_files:
  - split: train
    path: text_numinamath_cot/train-*
- config_name: text_openhermes_2_5
  data_files:
  - split: train
    path: text_openhermes_2_5/train-*
- config_name: text_openorca
  data_files:
  - split: train
    path: text_openorca/train-*
- config_name: text_orcamath
  data_files:
  - split: train
    path: text_orcamath/train-*
- config_name: text_pythoncode25k
  data_files:
  - split: train
    path: text_pythoncode25k/train-*
- config_name: text_pythoncodealpaca
  data_files:
  - split: train
    path: text_pythoncodealpaca/train-*
- config_name: text_ruozhiba
  data_files:
  - split: train
    path: text_ruozhiba/train-*
- config_name: text_theoremqa
  data_files:
  - split: train
    path: text_theoremqa/train-*
- config_name: text_wizardlm_evol
  data_files:
  - split: train
    path: text_wizardlm_evol/train-*
- config_name: textcaps
  data_files:
  - split: train
    path: textcaps/train-*
- config_name: textocr(gpt4v)
  data_files:
  - split: train
    path: textocr(gpt4v)/train-*
- config_name: textvqa
  data_files:
  - split: train
    path: textvqa/train-*
- config_name: tqa
  data_files:
  - split: train
    path: tqa/train-*
- config_name: unigeo(mathv360k)
  data_files:
  - split: train
    path: unigeo(mathv360k)/train-*
- config_name: ureader_cap
  data_files:
  - split: train
    path: ureader_cap/train-*
- config_name: ureader_ie
  data_files:
  - split: train
    path: ureader_ie/train-*
- config_name: ureader_kg_processed
  data_files:
  - split: train
    path: ureader_kg_processed/train-*
- config_name: ureader_qa_processed
  data_files:
  - split: train
    path: ureader_qa_processed/train-*
- config_name: vision_flan(filtered)
  data_files:
  - split: train
    path: vision_flan(filtered)/train-*
- config_name: vistext
  data_files:
  - split: train
    path: vistext/train-*
- config_name: visual7w
  data_files:
  - split: train
    path: visual7w/train-*
- config_name: visualmrc
  data_files:
  - split: train
    path: visualmrc/train-*
- config_name: visualwebinstruct(filtered)
  data_files:
  - split: train
    path: visualwebinstruct(filtered)/train-*
- config_name: vizwiz(mathv360k)
  data_files:
  - split: train
    path: vizwiz(mathv360k)/train-*
- config_name: vqaonbd
  data_files:
  - split: train
    path: vqaonbd/train-*
- config_name: vqarad
  data_files:
  - split: train
    path: vqarad/train-*
- config_name: vqav2
  data_files:
  - split: train
    path: vqav2/train-*
- config_name: vsr
  data_files:
  - split: train
    path: vsr/train-*
- config_name: websight
  data_files:
  - split: train
    path: websight/train-*
- config_name: wildvision
  data_files:
  - split: train
    path: wildvision/train-*
- config_name: wordart
  data_files:
  - split: train
    path: wordart/train-*
- config_name: yesbut
  data_files:
  - split: train
    path: yesbut/train-*
size_categories:
- 10M<n<100M
---

# Fine Vision

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6630afa2d40e9b46f95b4c15/8lfflTBHL2SAjcwPQjJSG.png)

FineVision is a massive collection of datasets with **17.3M images**, **24.3M samples**, **88.9M turns**, and **9.5B answer tokens**, designed for training state-of-the-art open Vision-Language-Models.

More detail can be found in the blog post: https://huggingface.co/spaces/HuggingFaceM4/FineVision


### Load the data
```python
  from datasets import load_dataset, get_dataset_config_names

  # Get all subset names and load the first one
  available_subsets = get_dataset_config_names('HuggingFaceM4/FineVision')
  ds = load_dataset('HuggingFaceM4/FineVision', name=available_subsets[0], split='train', streaming=True)
  
  # Inspect the first sample
  ds[0]
```

### Structure

```bash
{
  'images': [<PIL.PngImagePlugin.PngImageFile image mode=RGB size=387x194 at 0x7F8F0B308200>],
  'texts': [{'user': 'Question: What is between the reticulum and the abomasum?\nChoices:\nA. Intestine\nB. Omasum\nC. Stomach\nD. Rumen\nAnswer with the letter.', 'assistant': 'Answer: B'},
            {'user': 'Here is a diagram figure extracted from some Grade 1 - 6 science books.\nPlease first describe the content of this figure in detail, including how the knowledge visually displayed in the diagram.\nThen start with a section title "related knowledge:", briefly and concisely highlight the related domain knowledge and theories that underly this diagram. Note that you do not need to provide much detail. Simply cover the most important concepts.', 'assistant': "The figure is a simple diagram of the four compartments of a ruminant animal's stomach, which are the rumen, reticulum, omasum, and abomasum. The diagram shows the relative size and position of each compartment within the stomach, with arrows indicating the direction of food flow from one compartment to the next. \n\nRelated Knowledge:\n- Ruminant Digestion: Ruminants such as cows, sheep, and goats have a unique digestive system that allows them to break down fibrous plant material, like grass, that other animals cannot digest.\n- Four Stomach Compartments: The rumen is the largest compartment and serves as a fermentation vat where microbes break down fibrous material. The reticulum traps foreign objects and also helps in fermentation. The omasum absorbs water and nutrients, and the abomasum is the true stomach where digestion occurs similarly to monogastric animals.\n- Microbial Fermentation: The microbes in the rumen produce volatile fatty acids which are the primary energy source for ruminants. They also produce gases like methane, which are eructated (belched) out.\n- Ruminant Nutrition: Ruminants rely on a high-fiber diet and have to consume large quantities of forage to meet their nutritional needs."}],
  'source': 'original',
  'image_correspondence_ratings': [4, 3],
  'image_correspondence_min': 3,
  'visual_dependency_ratings': [4, 5],
  'visual_dependency_min': 4,
  'formatting_ratings': [4, 4],
  'formatting_min': 4,
  'relevance_ratings': [5, 5],
  'relevance_min': 5
}
```

### Categories

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6630afa2d40e9b46f95b4c15/Ge_nQPmVrxDy_Te7kUpdB.png)

### Licensing Information

Each of the publicly available sub-datasets present in FineVision are governed by specific licensing conditions. Therefore, when making use of them you must take into consideration each of the licenses governing each dataset. To the extent we have any rights in the prompts, these are licensed under CC-BY-4.0.

### Citation

If you find this dataset useful, please cite:
```
@misc{wiedmann2025finevisionopendataneed,
      title={FineVision: Open Data Is All You Need}, 
      author={Luis Wiedmann and Orr Zohar and Amir Mahla and Xiaohan Wang and Rui Li and Thibaud Frere and Leandro von Werra and Aritra Roy Gosthipaty and Andrés Marafioti},
      year={2025},
      eprint={2510.17269},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2510.17269}, 
}
```