| 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() | |