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Update app.py
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app.py
CHANGED
@@ -8,8 +8,8 @@ question_model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_s
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question_tokenizer = T5Tokenizer.from_pretrained('ramsrigouthamg/t5_squad_v1')
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def get_question(sentence,answer,mdl,tknizer):
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print (
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max_len = 256
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encoding = tknizer.encode_plus(text,max_length=max_len, pad_to_max_length=False,truncation=True, return_tensors="pt")
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@@ -32,8 +32,8 @@ def get_question(sentence,answer,mdl,tknizer):
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return Question
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ques = get_question(context,answer,question_model,question_tokenizer)
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print ("question: ",ques)
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@@ -41,23 +41,27 @@ print ("question: ",ques)
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import gradio as gr
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title = "Question Generator Three"
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description = "Paste or write a text.
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question = gr.outputs.Textbox( type="auto", label="Question")
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examples = [
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["""Fears of a new Covid-19 cluster linked to a hotpot restaurant have surfaced amid Hong Kong’s Omicron-fuelled fifth wave, while infections tied to an investment bank continued to expand, triggering the evacuation of residents in a building after vertical transmission of the virus was detected.
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On Wednesday, hundreds thronged Covid-19 testing stations in Tuen Mun, with some residents complaining of long waiting times and chaotic arrangements. Authorities have deemed the district a high-risk area because of a higher number of infections.
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Health officials said sewage testing would be conducted in Tuen Mun to monitor the spread of the coronavirus, but a string of preliminary-positive cases detected across the city suggested a wider, more worrying situation.
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""", "a higher number of infections"]
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]
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def generate_question(
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return get_question(
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iface = gr.Interface(
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fn=generate_question,
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inputs=[
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outputs=question, title=title, description=description, examples=examples)
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iface.launch(debug=False)
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question_tokenizer = T5Tokenizer.from_pretrained('ramsrigouthamg/t5_squad_v1')
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def get_question(sentence,answer,mdl,tknizer):
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prompt = "context: {} answer: {}".format(sentence,answer)
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print (prompt)
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max_len = 256
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encoding = tknizer.encode_plus(text,max_length=max_len, pad_to_max_length=False,truncation=True, return_tensors="pt")
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return Question
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Text = "Elon Musk said that Tesla will not accept payments in Bitcoin because of environmental concerns."
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Answer = "Elon Musk"
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ques = get_question(context,answer,question_model,question_tokenizer)
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print ("question: ",ques)
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import gradio as gr
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title = "Question Generator Three"
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description = "Paste or write a text. You may also paste or write a short answer, preferably a noun or noun phrase. Submit and the machine will attempt to generate a coherent question."
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Text = gr.inputs.Textbox(lines=5, placeholder="Enter paragraph/context here...")
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Answer = gr.inputs.Textbox(lines=3, placeholder="Enter answer/keyword here...")
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question = gr.outputs.Textbox( type="auto", label="Question")
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examples = [
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["""Fears of a new Covid-19 cluster linked to a hotpot restaurant have surfaced amid Hong Kong’s Omicron-fuelled fifth wave, while infections tied to an investment bank continued to expand, triggering the evacuation of residents in a building after vertical transmission of the virus was detected.
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On Wednesday, hundreds thronged Covid-19 testing stations in Tuen Mun, with some residents complaining of long waiting times and chaotic arrangements. Authorities have deemed the district a high-risk area because of a higher number of infections.
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Health officials said sewage testing would be conducted in Tuen Mun to monitor the spread of the coronavirus, but a string of preliminary-positive cases detected across the city suggested a wider, more worrying situation.
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""", "a higher number of infections"],
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["""Squid Game made history on Wednesday as the first non-English-language television series and the first Korean series to score a nomination for a Screen Actors Guild Award.
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The hit Netflix show, created by Hwang Dong-hyuk, is nominated for ensemble in a drama series alongside The Handmaid’s Tale, The Morning Show, Succession and Yellowstone.
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Squid Game stars Lee Jung-jae and Jung Ho-yeon also landed individual nominations for actor and actress in a drama series, respectively.
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""", "Yellowstone"]
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]
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def generate_question(Text,Answer):
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return get_question(Text,Answer,question_model,question_tokenizer)
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iface = gr.Interface(
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fn=generate_question,
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inputs=[Text,Answer],
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outputs=question, title=title, description=description, examples=examples)
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iface.launch(debug=False)
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