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import gradio as gr | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
# Load the model and tokenizer | |
model_name = "meta-llama/CodeLlama-7b-hf" | |
model = AutoModelForCausalLM.from_pretrained(model_name) | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
def generate_code(prompt): | |
inputs = tokenizer(prompt, return_tensors="pt") | |
outputs = model.generate(inputs["input_ids"], max_length=200) | |
code = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
return code | |
# Set up the Gradio interface | |
demo = gr.Interface(fn=generate_code, | |
inputs="text", | |
outputs="text", | |
title="CodeLlama 7B Model", | |
description="Generate code with CodeLlama-7b-hf.").launch() | |
demo.launch() | |