feat: loads the pre-trained weight from the official branch, related to

#10

README.md

@@ -35,14 +35,14 @@ Gradio web demos are available! [![Demo](https://img.shields.io/badge/Demo-Gradi
 
 |Task|Sec/Img|Score|Trained Model|<div id="demo">Demo</div>|
 |---|---|---|---|---|
-| [CORD](https://github.com/clovaai/cord) (Document Parsing)   |   0.7 /<br> 0.7 /<br> 1.2   |  93.9 /<br> 93.6 /<br> 93.5    | [donut-base-finetuned-cord-v2](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v2) (1280) /<br> [donut-base-finetuned-cord-v1](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1) (1280) /<br> [donut-base-finetuned-cord-v1-2560](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1-2560) | [gradio space web demo](https://huggingface.co/spaces/naver-clova-ix/donut-base-finetuned-cord-v2),<br>[google colab demo](https://colab.research.google.com/drive/1o07hty-3OQTvGnc_7lgQFLvvKQuLjqiw?usp=sharing) |
-| [Train Ticket](https://github.com/beacandler/EATEN) (Document Parsing)   |   0.6   |  98.8    | [donut-base-finetuned-zhtrainticket](https://huggingface.co/naver-clova-ix/donut-base-finetuned-zhtrainticket) | [google colab demo](https://colab.research.google.com/drive/16O-hMvGiXrYZnlXA_tfJ9_q760YcLoOj?usp=sharing) |
-| [RVL-CDIP](https://www.cs.cmu.edu/~aharley/rvl-cdip) (Document Classification)     |  0.75   |   95.3      | [donut-base-finetuned-rvlcdip](https://huggingface.co/naver-clova-ix/donut-base-finetuned-rvlcdip) | [google colab demo](https://colab.research.google.com/drive/1xUDmLqlthx8A8rWKLMSLThZ7oeRJkDuU?usp=sharing) |
-| [DocVQA Task1](https://rrc.cvc.uab.es/?ch=17) (Document VQA) |  0.78       | 67.5 | [donut-base-finetuned-docvqa](https://huggingface.co/naver-clova-ix/donut-base-finetuned-docvqa) | [google colab demo](https://colab.research.google.com/drive/1Z4WG8Wunj3HE0CERjt608ALSgSzRC9ig?usp=sharing) |
+| [CORD](https://github.com/clovaai/cord) (Document Parsing)   |   0.7 /<br> 0.7 /<br> 1.2   |  93.9 /<br> 93.6 /<br> 93.5    | [donut-base-finetuned-cord-v2](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v2/tree/official) (1280) /<br> [donut-base-finetuned-cord-v1](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1/tree/official) (1280) /<br> [donut-base-finetuned-cord-v1-2560](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1-2560/tree/official) | [gradio space web demo](https://huggingface.co/spaces/naver-clova-ix/donut-base-finetuned-cord-v2),<br>[google colab demo](https://colab.research.google.com/drive/1o07hty-3OQTvGnc_7lgQFLvvKQuLjqiw?usp=sharing) |
+| [Train Ticket](https://github.com/beacandler/EATEN) (Document Parsing)   |   0.6   |  98.8    | [donut-base-finetuned-zhtrainticket](https://huggingface.co/naver-clova-ix/donut-base-finetuned-zhtrainticket/tree/official) | [google colab demo](https://colab.research.google.com/drive/16O-hMvGiXrYZnlXA_tfJ9_q760YcLoOj?usp=sharing) |
+| [RVL-CDIP](https://www.cs.cmu.edu/~aharley/rvl-cdip) (Document Classification)     |  0.75   |   95.3      | [donut-base-finetuned-rvlcdip](https://huggingface.co/naver-clova-ix/donut-base-finetuned-rvlcdip/tree/official) | [google colab demo](https://colab.research.google.com/drive/1xUDmLqlthx8A8rWKLMSLThZ7oeRJkDuU?usp=sharing) |
+| [DocVQA Task1](https://rrc.cvc.uab.es/?ch=17) (Document VQA) |  0.78       | 67.5 | [donut-base-finetuned-docvqa](https://huggingface.co/naver-clova-ix/donut-base-finetuned-docvqa/tree/official) | [google colab demo](https://colab.research.google.com/drive/1Z4WG8Wunj3HE0CERjt608ALSgSzRC9ig?usp=sharing) |
 
 The links to the pre-trained backbones are here:
-- [`donut-base`](https://huggingface.co/naver-clova-ix/donut-base): trained with 64 A100 GPUs (~2.5 days), number of layers (encoder: {2,2,14,2}, decoder: 4), input size 2560x1920, swin window size 10, IIT-CDIP (11M) and SynthDoG (ECJK, 0.5M x 4).
-- [`donut-proto`](https://huggingface.co/naver-clova-ix/donut-proto): (preliminary model) trained with 8 V100 GPUs (~5 days), number of layers (encoder: {2,2,18,2}, decoder: 4), input size 2048x1536, swin window size 8, and SynthDoG (EJK, 0.4M x 3).
+- [`donut-base`](https://huggingface.co/naver-clova-ix/donut-base/tree/official): trained with 64 A100 GPUs (~2.5 days), number of layers (encoder: {2,2,14,2}, decoder: 4), input size 2560x1920, swin window size 10, IIT-CDIP (11M) and SynthDoG (ECJK, 0.5M x 4).
+- [`donut-proto`](https://huggingface.co/naver-clova-ix/donut-proto/tree/official): (preliminary model) trained with 8 V100 GPUs (~5 days), number of layers (encoder: {2,2,18,2}, decoder: 4), input size 2048x1536, swin window size 8, and SynthDoG (EJK, 0.4M x 3).
 
 Please see [our paper](#how-to-cite) for more details.
 

donut/model.py

@@ -592,7 +592,7 @@ def from_pretrained(
                 Name of a pretrained model name either registered in huggingface.co. or saved in local,
                 e.g., `naver-clova-ix/donut-base`, or `naver-clova-ix/donut-base-finetuned-rvlcdip`
         """
-        model = super(DonutModel, cls).from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
+        model = super(DonutModel, cls).from_pretrained(pretrained_model_name_or_path, revision="official", *model_args, **kwargs)
 
         # truncate or interplolate position embeddings of donut decoder
         max_length = kwargs.get("max_length", model.config.max_position_embeddings)