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+ ---
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+ license: afl-3.0
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+ ---
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+
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+ # Question generation using T5 transformer trained on SQuAD
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+
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+ <h2> <i>Input format: context: "..." answer(optional): "..." </i></h2>
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+
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+ Import the pretrained model as well as tokenizer:
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+ ```
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+ from transformers import T5ForConditionalGeneration, T5Tokenizer
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+
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+ model = T5ForConditionalGeneration.from_pretrained('AbhilashDatta/T5_qgen-squad_v2')
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+ tokenizer = T5Tokenizer.from_pretrained('AbhilashDatta/T5_qgen-squad_v2')
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+ ```
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+
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+ Then use the tokenizer to encode/decode and model to generate:
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+
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+ ```
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+ input = "context: My name is Abhilash Datta. answer: Abhilash"
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+ batch = tokenizer(input, padding='longest', max_length=512, return_tensors='pt')
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+ inputs_batch = batch['input_ids'][0]
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+ inputs_batch = torch.unsqueeze(inputs_batch, 0)
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+
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+ ques_id = model.generate(inputs_batch, max_length=100, early_stopping=True)
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+ ques_batch = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in ques_id]
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+
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+ print(ques_batch)
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+ ```
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+
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+ Output:
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+ ```
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+ ['what is my name']
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+ ```