Create app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+
+from transformers import pipeline
+from PIL import Image
+
+model = "pacman2223/test-mod"
+
+image = Image.open("./sample_cv.png")
+image.save("cv.png")
+image = Image.open("./sample_hack.png")
+image.save("hack.png")
+
+def demo_process(img, question):
+
+    qa_pipeline = pipeline("document-question-answering", model=model)
+    qa_pipeline(img, question)
+
+    return qa_pipeline["answer"]
+
+
+demo = gr.Interface(
+    fn=demo_process,
+    inputs=["image", "text"],
+    outputs="json",
+    title=f"BIP demonstration for `layoutlmv2` task",
+    description="""This model is trained with 1200 receipt images of Docqva dataset. <br>""",
+    examples=[["cv.png"], ["hack.png"]],
+    cache_examples=False,
+)
+
+demo.launch()