adapt c2t docs (#4288)

* fix pp-c2t download

* adapt C2T docs

docs/module_usage/tutorials/vlm_modules/chart_parsing.en.md

@@ -23,12 +23,13 @@ Multimodal chart parsing is a cutting-edge technology in the OCR field, focusing
 <td>PP-Chart2Table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-Chart2Table_infer.tar">Inference Model</a></td>
 <td>0.58</td>
 <td>1.4</td>
-<th>75.98</th>
-<td>PP-Chart2Table is a self-developed multimodal model by the PaddlePaddle team, focusing on chart parsing, demonstrating outstanding performance in both Chinese and English chart parsing tasks. The team adopted a carefully designed data generation strategy, constructing a high-quality multimodal dataset of nearly 700,000 entries covering common chart types like pie charts, bar charts, stacked area charts, and various application scenarios. They also designed a two-stage training method, utilizing large model distillation to fully leverage massive unlabeled OOD data. In internal business tests in both Chinese and English scenarios, PP-Chart2Table not only achieved the SOTA level among models of the same parameter scale but also reached accuracy comparable to 7B parameter scale VLM models in critical scenarios.</td>
+<th>80.60</th>
+<td>PP-Chart2Table is a SOTA multimodal model developed by the PaddlePaddle team, specializing in chart parsing for both Chinese and English. Its high performance is driven by a novel "Shuffled Chart Data Retrieval" training task, which, combined with a refined token masking strategy, significantly improves its efficiency in converting charts to data tables. The model is further strengthened by an advanced data synthesis pipeline that uses high-quality seed data, RAG, and LLMs persona design to create a richer, more diverse training set. To address the challenge of large-scale unlabeled, out-of-distribution (OOD) data, the team implemented a two-stage distillation process, ensuring robust adaptability and generalization on real-world data. In-house benchmarks demonstrate that PP-Chart2Table not only outperforms models of a similar scale but also achieves accuracy on par with 7-billion parameter Vision Language Models (VLMs) in critical applications.</td>
 </tr>
 </table>
 
 <b>Note: The above model scores are the results of internal evaluation set model testing, with a total of 1801 data points, including various chart types such as bar charts, line charts, and pie charts for testing samples under various scenarios such as financial reports, laws and regulations, contracts, etc. There are currently no plans to make them public.</b>
+> ❗ <b>Note</b>：The PP-Chart2Table model was upgraded on June 27, 2025. If you need to use the weights from the previous version of the model, please click the <a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-Chart2Table_infer.bak.tar">download link</a>
 
 
 

docs/module_usage/tutorials/vlm_modules/chart_parsing.md

@@ -24,13 +24,13 @@ comments: true
 <td>PP-Chart2Table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-Chart2Table_infer.tar">推理模型</a></td>
 <td>0.58</td>
 <td>1.4</td>
-<th>75.98</th>
-<td>PP-Chart2Table是飞桨团队自研的一款专注于图表解析的多模态模型，在中英文图表解析任务中展现出卓越性能。团队采用精心设计的数据生成策略，构建了近70万条高质量的图表解析多模态数据集，全面覆盖饼图、柱状图、堆叠面积图等常见图表类型及各类应用场景。同时设计了二阶段训练方法，结合大模型蒸馏实现对海量无标注OOD数据的充分利用。在内部业务的中英文场景测试中，PP-Chart2Table不仅达到同参数量级模型中的SOTA水平，更在关键场景中实现了与7B参数量级VLM模型相当的精度。</td>
+<th>80.60</th>
+<td>PP-Chart2Table是飞桨团队自研的一款专注于图表解析的多模态模型，在中英文图表解析任务中展现出卓越性能。团队专为图表解析设计了Shuffled Chart Data Retrieval训练任务，并结合精心设计的令牌掩码策略，显著提升其在图表转数据表任务上的性能。此外，团队通过精心设计的数据合成流程增强了PP-Chart2Table的能力，该流程利用高质量的种子数据，并结合RAG和大语言模型人格设计，以生成更丰富多样化的数据。为了处理大量未标记的分布外 (OOD) 数据，团队采用了两阶段大模型蒸馏训练过程，确保模型在广泛的真实世界数据集中具有出色的适应性和泛化能力。在内部业务的中英文场景测试中，PP-Chart2Table不仅达到同参数量级模型中的SOTA水平，更在关键场景中实现了与7B参数量级VLM模型相当的精度。</td>
 </tr>
 </table>
 
 <b>注：以上模型分数为内部评估集模型测试结果，共1801条数据，包括了各个场景（财报、法律法规、合同等）下的各种图表类型（柱状图、折线图、饼图等）的测试样本，暂时未有计划公开。</b>
-
+> ❗ <b>注</b>：PP-Chart2Table模型于 2025.6.27 升级，如需使用升级前的模型权重，请点击<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-Chart2Table_infer.bak.tar">下载链接</a>
 
 
 ## 三、快速集成