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Update app.py
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app.py
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@@ -47,7 +47,7 @@ out=grad.Textbox(lines=1, label="Generated Tensors")
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grad.Interface(generate, inputs=txt, outputs=out).launch()
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'''
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from transformers import GPT2LMHeadModel,GPT2Tokenizer
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import gradio as grad
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@@ -67,3 +67,27 @@ def generate(starting_text):
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txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
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out=grad.Textbox(lines=1, label="Generated Tensors")
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grad.Interface(generate, inputs=txt, outputs=out).launch()
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grad.Interface(generate, inputs=txt, outputs=out).launch()
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'''
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'''5.12
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from transformers import GPT2LMHeadModel,GPT2Tokenizer
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import gradio as grad
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txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
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out=grad.Textbox(lines=1, label="Generated Tensors")
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grad.Interface(generate, inputs=txt, outputs=out).launch()
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'''
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#5.20
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from transformers import AutoModelWithLMHead, AutoTokenizer
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import gradio as grad
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text2text_tkn = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
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mdl = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
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def text2text(context,answer):
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input_text = "answer: %s context: %s </s>" % (answer, context)
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features = text2text_tkn ([input_text], return_tensors='pt')
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output = mdl.generate(input_ids=features['input_ids'],
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attention_mask=features['attention_mask'],
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max_length=64)
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response=text2text_tkn.decode(output[0])
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return response
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context=grad.Textbox(lines=10, label="English", placeholder="Context")
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ans=grad.Textbox(lines=1, label="Answer")
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out=grad.Textbox(lines=1, label="Genereated Question")
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grad.Interface(text2text, inputs=[context,ans], outputs=out).launch()
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