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app.py

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+import os 
+import gradio as gr
+
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+#question_model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_squad_v1')
+#question_tokenizer = T5Tokenizer.from_pretrained('t5-base')
+question_model = T5ForConditionalGeneration.from_pretrained('t5-small')
+question_tokenizer = T5Tokenizer.from_pretrained('t5-small')
+
+def get_question(context, answer):
+    text = "context: {} answer: {}".format(context, answer)
+    #max_len = 512
+    #encoding = question_tokenizer.encode_plus(text, max_length=max_len, padding='max_length', truncation=True, return_tensors="pt")
+    encoding = question_tokenizer.encode_plus(text, return_tensors="pt")
+    input_ids, attention_mask = encoding["input_ids"], encoding["attention_mask"]
+    outs = question_model.generate(input_ids=input_ids,
+                                    attention_mask=attention_mask,
+                                    early_stopping=True,
+                                    num_beams=3, # Use fewer beams to generate fewer but higher-quality questions
+                                    num_return_sequences=3,
+                                    no_repeat_ngram_size=3, # Allow some repetition to avoid generating nonsensical questions
+                                    max_length=256) # Use a shorter max length to focus on generating more relevant questions
+    dec = [question_tokenizer.decode(ids) for ids in outs]
+    questions = ""
+    for i, question in enumerate(dec):
+        question = question.replace("question:", "").replace("<pad>", "").replace("</s>", "")
+        question = question.strip()
+        questions += question
+        if i != len(dec)-1:
+            questions += "§"
+    return questions
+
+input_context = gr.Textbox()
+input_answer = gr.Textbox()
+output_question = gr.Textbox()
+
+interface = gr.Interface(
+    fn=get_question,
+    inputs=[input_context, input_answer],
+    outputs=output_question
+)
+
+interface.launch()

requirements.txt

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+transformers
+sentencepiece
+torch