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import gradio as gr
# Load the text-generation pipeline with Mistral model
from langchain_huggingface import HuggingFaceEndpoint
# Initialize the LLM and other components
llm = HuggingFaceEndpoint(
repo_id="mistralai/Mistral-7B-Instruct-v0.3",
task="text-generation",
max_new_tokens=4096,
temperature=0.5,
do_sample=False,
)
# Define the function to process user input
def classify_text(text):
prompt = "Classify the following text into a category or topic:"
input_text = f"{prompt}\n{text}"
results = llm.invoke(input_text)
return results
# Create Gradio interface
interface = gr.Interface(
fn=classify_text,
inputs=gr.Textbox(lines=4, placeholder="Enter your text here..."),
outputs=gr.Textbox(lines=4),
title="Text Classification with Mistral",
description="Enter some text to classify it into a category or topic using the Mistral-7B-Instruct-v0.3 model."
)
# Launch the app
if __name__ == "__main__":
interface.launch()
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