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b853635
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Parent(s):
fa6445f
Update app.py
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app.py
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import gradio as gr
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import gradio as gr
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from transformers import pipeline
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# Load the model
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qa_pipeline = pipeline("question-answering", model="william4416/bewtesttwo")
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# Define the function to process the JSONL file
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def process_jsonl(file_path):
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with open(file_path, "r", encoding="utf-8") as f:
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data = f.readlines()
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return [eval(line) for line in data]
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# Define the function to answer questions from the model
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def answer_question(context, question):
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# Process the context from the JSONL file
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contexts = [item["context"] for item in context]
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# Perform question answering
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answers = []
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for ctxt in contexts:
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answer = qa_pipeline(question=question, context=ctxt)
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answers.append(answer["answer"])
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return answers
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# Create the interface
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context_input = gr.inputs.File(label="utsdata.jsonl")
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question_input = gr.inputs.Textbox(label="Enter your question", lines=3)
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output_text = gr.outputs.Textbox(label="Answer")
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# Create the interface
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gr.Interface(
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fn=answer_question,
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inputs=[context_input, question_input],
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outputs=output_text,
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title="Question Answering with Hugging Face Transformers",
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description="Upload a JSONL file containing contexts and ask a question to get answers.",
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).launch()
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