llama.py

import torch
from transformers import LLaMAForCausalLM, LLaMATokenizer

model_name = "llama-3.1"
tokenizer = LLaMATokenizer.from_pretrained(model_name)
model = LLaMAForCausalLM.from_pretrained(model_name)

def analyze_code(code):
    # Preprocess code for LLaMA 3.1
    inputs = tokenizer.encode_plus(code, return_tensors="pt")

    # Run code analysis using LLaMA 3.1
    outputs = model.generate(inputs["input_ids"], max_length=512)

    # Return analyzed code representation
    return outputs.last_hidden_state