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@@ -31,12 +31,12 @@ In the following table, we provide all models [🤗 link] of the TokenOCR series
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  | [R50]() | Backbone is ResNet-50 |
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  | [TokenOCR-2048-Bilingual-seg]() | feature dimension is 2048; support interactive with English and Chinese texts. |
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  | [TokenOCR-4096-English-seg](https://huggingface.co/TongkunGuan/TokenOCR_4096_English_seg) | feature dimension is 2048; only support interactive with English texts (We recommend). |
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-
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  ### Quick Start
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- <!-- > \[!Warning\]
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- > 🚨 Note: In our experience, the `TokenOCR-2048-Bilingual` series is better suited for building MLLMs than the `-seg` version. -->
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  ```python
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  import os
@@ -87,8 +87,7 @@ generate_similiarity_map(images, attn_map, all_bpe_strings, out_dir, target_aspe
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  """user command """
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  # python quick_start.py
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  ```
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-
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-
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  <!-- # Introduction -->
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  <h2 style="color: #4CAF50;">Introduction</h2>
 
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  | [R50]() | Backbone is ResNet-50 |
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  | [TokenOCR-2048-Bilingual-seg]() | feature dimension is 2048; support interactive with English and Chinese texts. |
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  | [TokenOCR-4096-English-seg](https://huggingface.co/TongkunGuan/TokenOCR_4096_English_seg) | feature dimension is 2048; only support interactive with English texts (We recommend). |
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+ </center>
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  ### Quick Start
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+ > \[!Warning\]
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+ > 🚨 Note: Since there are fewer Chinese images in public data than English, we recommend you use the **`TokenOCR-4096-English-seg`** version.
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  ```python
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  import os
 
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  """user command """
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  # python quick_start.py
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  ```
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+ <center>
 
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  <!-- # Introduction -->
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  <h2 style="color: #4CAF50;">Introduction</h2>