Improve model card and add metadata (#1)
Browse files- Improve model card and add metadata (0d7b2dffe5726f5b9f4351085071b025b162ef02)
Co-authored-by: Niels Rogge <[email protected]>
README.md
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license: apache-2.0
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---
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license: apache-2.0
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pipeline_tag: image-text-to-text
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library_name: transformers
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---
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# SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models
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This model, VLAA-Thinker-Qwen2VL-7B, is a vision-language model fine-tuned on the VLAA-Thinking dataset. As described in [](https://huggingface.co/papers/2504.11468), it leverages a combination of supervised fine-tuning (SFT) and reinforcement learning (RL) to improve reasoning capabilities in LLMs. The model excels in multimodal reasoning tasks, achieving state-of-the-art performance on the OpenCompass Multimodal Reasoning Leaderboard as of April 7th, 2025.
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<p align="center">
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π <a href="https://ucsc-vlaa.github.io/VLAA-Thinking/" target="_blank">Project Page</a>
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β’ <img src="./assets/ar.svg" alt="Arxiv Logo" style="height: 1em; vertical-align: middle; margin-right: 0.3em;">
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<a href="./assets/VLAA-Thinker.pdf" target="_blank">Arxiv</a>
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β’ π» <a href="https://github.com/UCSC-VLAA/VLAA-Thinking" target="_blank">Code</a>
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</p>
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Both **VLAA-Thinker-Qwen2.5-3B** and **VLAA-Thinker-Qwen2.5-7B** achieve **SOTA** performance on [OpenCompass Multimodal Reasoning Leaderboard](https://rank.opencompass.org.cn/leaderboard-multimodal-reasoning/?m=REALTIME) as of April 7th, 2025.
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<img src="assets/opencompass_4b_box.png" width = "640" alt="pipeline" align=center />
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-----
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<img src="assets/opencompass_7b_box.png" width = "640" alt="pipeline" align=center />
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## Quick Start π
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### Inference
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Run `python inference.py`. Note that our model is trained with a system prompt. Please ensure that it is included for inference.
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### Dataset Download
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Run `bash ./utils/download_dataset.sh`. Specify the dataset root with absolute path. The dataset should be ordered as follows:
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```
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βββ VLAA-Thinking-SFT-126K.json
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βββ VLAA-Thinking-GRPO-25K.json
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βββ images
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βββ allava_laion
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βββ arxivqa
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βββ chartqa
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βββ clevr_math
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βββ coco
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β βββ train2017
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βββ docvqa
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βββ geoqa170k
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βββ synthesis
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βββ vg
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β βββ VG_100K
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β βββ VG_100K_2
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βββ vizwiz
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```
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### Training
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Code coming soon!
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(Rest of the README content can be kept as is)
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