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1from transformers import AutoModelForCausalLM, AutoTokenizer
2import torch
3
4model_id = "lablab-ai-amd-developer-hackathon/security-auditor-14b"
5tokenizer = AutoTokenizer.from_pretrained(model_id)
6model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
7
8💬 Example Usage
9messages = [
10 {"role": "user", "content": "Audit this C code for security issues:\n\n<code>\nvoid foo(char* buf, char* input) { strcpy(buf, input); }\n</code>"}
11]
12prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
13inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
14
15with torch.no_grad():
16 output = model.generate(**inputs, max_new_tokens=256, temperature=0.2)
17
18print(tokenizer.decode(output[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))