Upload app.py

app.py

@@ -1,5 +1,6 @@
 import os
 os.system('pip install transformers==4.25.1')
+os.system('pip install sentencepiece')
 # workaround: install old version of pytorch since detectron2 hasn't released packages for pytorch 1.9 (issue: https://github.com/facebookresearch/detectron2/issues/3158)
 os.system('pip install torch==1.8.1+cpu torchvision==0.9.1+cpu torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html')
 # install detectron2 that matches pytorch 1.8
@@ -79,7 +80,6 @@ def infer(image):
 
     return image
 
-
 title = "Interactive demo: layoutxlm-ja"
 description = "Demo for Microsoft's layoutxlm-ja, a Transformer for state-of-the-art document image understanding tasks. For More Information - https://huggingface.co/microsoft/layoutxlm-base. This particular model is fine-tuned on XFUND japanese, a dataset of manually annotated forms. It annotates the words appearing in the image as QUESTION/ANSWER/HEADER/OTHER. To use it, simply upload an image or use the example image below and click 'Submit'. Results will show up in a few seconds. If you want to make the output bigger, right-click on it and select 'Open image in new tab'."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2104.08836' target='_blank'>LayoutXLM: LayoutXLM is a multilingual variant of LayoutLMv2. Pre-training for Visually-Rich Document Understanding</a> | <a href='https://github.com/microsoft/unilm' target='_blank'>Github Repo</a></p>"