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# import gradio as gr
# gr.Interface.load("models/NousResearch/Yarn-Mistral-7b-128k").launch()
import gradio as gr
from transformers import pipeline
# Load a small GPT model fine-tuned for Python code generation
# generator = pipeline('text-generation', model='microsoft/CodeGPT-small-py')
generator = pipeline('text-generation', model='NousResearch/Yarn-Mistral-7b-128k')
def generate_code(prompt):
# Generate code from the model
responses = generator(prompt, max_length=500, num_return_sequences=1, temperature=0.1)
return responses[0]['generated_text']
input_textbox = gr.Textbox(label="Please click any button below or enter the last 4 digits of your Amazon.in order-id, name and email along with your questions. We shall get back to you!", lines=3)
outputs = gr.Markdown(label="Generated Code")
title = "Schogini Toys - AI Chatbot V2.03"
# Create a Gradio Interface
iface = gr.Interface(
fn=generate_code,
inputs=input_textbox, #[gr.Textbox(lines=10, label="Type your code description here")],
outputs=outputs, #[gr.Textbox(label="Generated Code")],
examples=[["Define a Python function to calculate factorial."]],
title=title,
)
# Run the interface
if __name__ == "__main__":
iface.launch()
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