10
stars
5
commits
2
linked in READMEs
Mar 8, 2024
updated
Accelerating the development of large-scale multi-modality models (LMMs) with
lmms-eval
π Homepage | π Documentation | π€ Huggingface Datasets
This is a formatted version of LLaVA-Bench(wild) that is used in LLaVA. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.
@misc{liu2023improvedllava,
author={Liu, Haotian and Li, Chunyuan and Li, Yuheng and Lee, Yong Jae},
title={Improved Baselines with Visual Instruction Tuning},
publisher={arXiv:2310.03744},
year={2023},
}
@inproceedings{liu2023llava,
author = {Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae},
title = {Visual Instruction Tuning},
booktitle = {NeurIPS},
year = {2023}
}
5 commits
10
stars
5
commits
2
linked in READMEs
Mar 8, 2024
updated
Accelerating the development of large-scale multi-modality models (LMMs) with
lmms-eval
π Homepage | π Documentation | π€ Huggingface Datasets
This is a formatted version of LLaVA-Bench(wild) that is used in LLaVA. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.
@misc{liu2023improvedllava,
author={Liu, Haotian and Li, Chunyuan and Li, Yuheng and Lee, Yong Jae},
title={Improved Baselines with Visual Instruction Tuning},
publisher={arXiv:2310.03744},
year={2023},
}
@inproceedings{liu2023llava,
author = {Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae},
title = {Visual Instruction Tuning},
booktitle = {NeurIPS},
year = {2023}
}
5 commits