IT5 model

app.py

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+import gradio as gr
+from transformers import pipeline
+
+nlp_t2t = pipeline(
+    'text2text-generation',
+    model='z-uo/it5-squadv1-it',
+    tokenizer='z-uo/it5-squadv1-it'
+)
+
+def start(question, context):
+    text = question + '\n' + context
+    response = nlp_t2t(text)
+
+    return response[0]['generated_text']
+
+
+face = gr.Interface(
+    fn=start,
+    inputs=[
+        gr.inputs.Textbox(lines=1, placeholder="Question Here… "),
+        gr.inputs.Textbox(lines=10, placeholder="Context Here… ")
+    ],
+    outputs=[
+        gr.outputs.Textbox(label="Answer"),
+    ]
+)
+
+face.launch(share=True)

requirements.txt

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+gradio
+torch
+transformers
+sentencepiece