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import gradio as gr
from transformers import pipeline
# Load your fine-tuned model from Hugging Face Hub
model_id = "peterjandre/finetuned-codet5-vbnet-csharp"
# Use text2text-generation pipeline (suitable for CodeT5)
generator = pipeline("text2text-generation", model=model_id)
def generate_code(prompt):
if not prompt:
return "Please enter a prompt."
outputs = generator(prompt, max_length=256, num_return_sequences=1)
return outputs[0]['generated_text']
# Build Gradio interface
iface = gr.Interface(
fn=generate_code,
inputs=gr.Textbox(lines=5, placeholder="Enter code prompt here..."),
outputs="textbox",
title="CodeT5 VBNet/C# Code Generator",
description="Generate VB.NET or C# code from your prompt using a fine-tuned CodeT5 model."
)
if __name__ == "__main__":
iface.launch()
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