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+- config_name: DocVQA + features: + - name: questionId + dtype: string + - name: question + dtype: string + - name: question_types + sequence: string + - name: image + dtype: image + - name: docId + dtype: int64 + - name: ucsf_document_id + dtype: string + - name: ucsf_document_page_no + dtype: string + - name: answers + sequence: string + - name: data_split + dtype: string + splits: + # - name: train + # num_bytes: 5659006943.631 + # num_examples: 39463 + - name: validation + num_bytes: 2532447207.066 + num_examples: 5349 + - name: test + num_bytes: 2500408525.732 + num_examples: 5188 + download_size: 9555791945 + dataset_size: 10691862676.428999 +- config_name: InfographicVQA + features: + - name: questionId + dtype: string + - name: question + dtype: string + - name: answers + sequence: string + - name: answer_type + sequence: string + - name: image + dtype: image + - name: image_url + dtype: string + - name: operation/reasoning + sequence: string + - name: ocr + dtype: string + - name: data_split + dtype: string + splits: + # - name: train + # num_bytes: 11559694546.32 + # num_examples: 23946 + - name: validation + num_bytes: 1863177404.253 + num_examples: 2801 + - name: test + num_bytes: 1851304047.712 + num_examples: 3288 + download_size: 2544892079 + dataset_size: 15274175998.285 +configs: +- config_name: DocVQA + data_files: + # - split: train + # path: DocVQA/train-* + - split: validation + path: DocVQA/validation-* + - split: test + path: DocVQA/test-* +- config_name: InfographicVQA + data_files: + # - split: train + # path: InfographicVQA/train-* + - split: validation + path: InfographicVQA/validation-* + - split: test + path: InfographicVQA/test-* +--- + +

+ +

+ +# Large-scale Multi-modality Models Evaluation Suite + +> Accelerating the development of large-scale multi-modality models (LMMs) with `lmms-eval` + +🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab) + +# This Dataset + +This is a formatted version of [DocVQA](https://arxiv.org/abs/2007.00398). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models. + +``` +@article{mathew2020docvqa, + title={DocVQA: A Dataset for VQA on Document Images. CoRR abs/2007.00398 (2020)}, + author={Mathew, Minesh and Karatzas, Dimosthenis and Manmatha, R and Jawahar, CV}, + journal={arXiv preprint arXiv:2007.00398}, + year={2020} +} +```