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license: apache-2.0
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Jinyue Chen*, Lingyu Kong*, [Haoran Wei](https://scholar.google.com/citations?user=J4naK0MAAAAJ&hl=en), Chenglong Liu, [Zheng Ge](https://joker316701882.github.io/), Liang Zhao, [Jianjian Sun](https://scholar.google.com/citations?user=MVZrGkYAAAAJ&hl=en), Chunrui Han, [Xiangyu Zhang](https://scholar.google.com/citations?user=yuB-cfoAAAAJ&hl=en)
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[Github](https://github.com/LingyvKong/OneChart)
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license: apache-2.0
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<h1><a href="https://github.com/LingyvKong/OneChart">OneChart: Purify the Chart Structural Extraction via One Auxiliary Token</a></h1>
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Jinyue Chen*, Lingyu Kong*, [Haoran Wei](https://scholar.google.com/citations?user=J4naK0MAAAAJ&hl=en), Chenglong Liu, [Zheng Ge](https://joker316701882.github.io/), Liang Zhao, [Jianjian Sun](https://scholar.google.com/citations?user=MVZrGkYAAAAJ&hl=en), Chunrui Han, [Xiangyu Zhang](https://scholar.google.com/citations?user=yuB-cfoAAAAJ&hl=en)
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[Github](https://github.com/LingyvKong/OneChart)
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[arxiv](https://arxiv.org/abs/2404.09987)
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## Quickly try the demo using hugginface:
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```python
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from transformers import AutoModel, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained('kppkkp/OneChart', trust_remote_code=True, use_fast=False, padding_side="right")
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model = AutoModel.from_pretrained('kppkkp/OneChart', trust_remote_code=True, low_cpu_mem_usage=True, device_map='cuda')
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model = model.eval().cuda()
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# input your test image
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image_file = 'image.png'
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res = model.chat(tokenizer, image_file, reliable_check=True)
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print(res)
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```
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