app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load your fine-tuned model and tokenizer
model_name = "EmTpro01/codellama-Code-Generator"  # Use your model name here
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to generate code from a prompt
def generate_code(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(inputs.input_ids, max_length=150, temperature=0.7, top_k=50)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Create the Gradio interface
interface = gr.Interface(
    fn=generate_code, 
    inputs="text", 
    outputs="text", 
    title="Code Generator",
    description="Enter a code prompt to generate Python code using the fine-tuned model."
)

# Launch the app
interface.launch()