--- dataset_info: features: - name: image dtype: image - name: id dtype: string - name: filepath dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string - name: blip_caption dtype: string - name: url dtype: string splits: - name: train num_bytes: 32275649949.488 num_examples: 558128 download_size: 27864965211 dataset_size: 32275649949.488 configs: - config_name: default data_files: - split: train path: data/train-* license: other language: - pt pretty_name: ViTucano-Pretrain task_categories: - image-to-text - text-generation size_categories: - 100K" }, { "from": "gpt", "value": "Selecione móveis de luxo 3 - colchão de espuma de memória de gel de polegada" } ], "blip_caption": "Selecione móveis de luxo 3 - colchão de espuma de memória de gel de polegada", "url": "http://ec1.ostkcdn.com/images/products/8111140/P15459545.jpg" } ``` ### Data Splits Available splits are `train`. ```python from datasets import load_dataset dataset = load_dataset("TucanoBR/ViTucano-Pretrain", split='train') # If you don't want to download the entire dataset, set streaming to `True` dataset = load_dataset("TucanoBR/ViTucano-Pretrain", split='train', streaming=True) ``` ## Dataset Creation ### Curation Rationale This dataset is a translation of the original [liuhaotian/LLaVA-Pretrain](https://huggingface.co./datasets/liuhaotian/LLaVA-Pretrain) obtained via Google's translation API. ### Source Data #### Who are the source language producers? All text samples translated from English to Portuguese. ### Annotations #### Annotation process Read this [dataset card](https://huggingface.co./datasets/liuhaotian/LLaVA-Pretrain) for more information. #### Who are the annotators? Read this [dataset card](https://huggingface.co./datasets/liuhaotian/LLaVA-Pretrain) for more information. ### Considerations for Using the Data **Warning:** This dataset may contain NSFW (Not Safe For Work) content, including explicit images and text captions with offensive/sensitive language. ### Other Known Limitations This dataset has has been translated using translation engines, potentially resulting in corrupted samples. While useful for quickly converting text between languages, translation engines often struggle with accurately preserving the syntax, semantics, and context of certain languages. ## Additional Information ### Dataset Curators [Nicholas Kluge Corrêa](mailto:kluge@uni-bonn.de). ### Licensing Information Users of this dataset must comply with license of [CC-3M](https://github.com/google-research-datasets/conceptual-captions/blob/master/LICENSE) and [BLIP](https://github.com/salesforce/BLIP/blob/main/LICENSE.txt) (if you use their synthetic caption). ### Licensing Information Creative Commons Attribution 4.0 International; and it should abide by the [policy of OpenAI](https://openai.com/policies/terms-of-use). ### Citation Information #### ViTucano ```bibtex @misc{correa20204vitucano, author={Corr{\^e}a, Nicholas Kluge and Sen, Aniket and Falk, Sophia and Fatimah, Shiza}, title={{ViTucano: A Portuguese Vision Assitant}}, year=2024, howpublished = {\url{https://huggingface.co./TucanoBR}}, } ``` #### Tucano ```bibtex @misc{correa2024tucanoadvancingneuraltext, title={{Tucano: Advancing Neural Text Generation for Portuguese}}, author={Corr{\^e}a, Nicholas Kluge and Sen, Aniket and Falk, Sophia and Fatimah, Shiza}, year={2024}, eprint={2411.07854}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2411.07854}, } ``` #### TinyLLaVA Factory ```bibtex @article{jia2024tinyllava, title={TinyLLaVA Factory: A Modularized Codebase for Small-scale Large Multimodal Models}, author={Jia, Junlong and Hu, Ying and Weng, Xi and Shi, Yiming and Li, Miao and Zhang, Xingjian and Zhou, Baichuan and Liu, Ziyu and Luo, Jie and Huang, Lei and Wu, Ji}, journal={arXiv preprint arXiv:2405.11788}, year={2024} } ``` #### LLaVA ```bibtex @misc{liu2023llava, title={Visual Instruction Tuning}, author={Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae}, publisher={NeurIPS}, year={2023}, } ``` ### Aknowlegments We gratefully acknowledge the granted access to the [Marvin cluster](https://www.hpc.uni-bonn.de/en/systems/marvin) hosted by [University of Bonn](https://www.uni-bonn.de/en) along with the support provided by its High Performance Computing \& Analytics Lab. ### Contributions If you want to contribute, contact me at [kluge@uni-bonn.de](mailto:kluge@uni-bonn.de)!