Delete app.py

app.py

@@ -1,38 +0,0 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import gradio as gr
-from transformers import pipeline
-import jsonl
-
-# Load the model
-qa_pipeline = pipeline("question-answering", model="william4416/bewtesttwo")
-
-# Define the function to process the JSONL file
-def process_jsonl(file_path):
-    with open(file_path, "r", encoding="utf-8") as f:
-        data = f.readlines()
-    return [eval(line) for line in data]
-
-# Define the function to answer questions from the model
-def answer_question(context, question):
-    # Process the context from the JSONL file
-    contexts = [item["context"] for item in context]
-    # Perform question answering
-    answers = []
-    for ctxt in contexts:
-        answer = qa_pipeline(question=question, context=ctxt)
-        answers.append(answer["answer"])
-    return answers
-
-# Create the interface
-context_input = gr.inputs.File(label="utsdata.jsonl")
-question_input = gr.inputs.Textbox(label="Enter your question", lines=3)
-output_text = gr.outputs.Textbox(label="Answer")
-
-# Create the interface
-gr.Interface(
-    fn=answer_question,
-    inputs=[context_input, question_input],
-    outputs=output_text,
-    title="Question Answering with Hugging Face Transformers",
-    description="Upload a JSONL file containing contexts and ask a question to get answers.",
-).launch()