Task	Description	Output
race_c	C/C++ OpenMP data race detection	yes / no
race_fortran	Fortran OpenMP data race detection	yes / no
mlperf	HPC benchmark factual QA	Short factual answer
plp	Programming language processing QA	Descriptive answer

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "swaggy/Qwen2.5-0.5B-HARGO-HPC"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")

messages = [
    {"role": "system", "content": "You are an expert in parallel programming and data race detection. Given a C/C++ code snippet with OpenMP directives, determine whether a data race exists. Answer ONLY 'yes' or 'no'."},
    {"role": "user", "content": "<your code snippet here>"},
]

inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(model.device)
outputs = model.generate(inputs, max_new_tokens=64, do_sample=False)
print(tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True))

Training

Base model: Qwen2.5-0.5B-Instruct
Stage 1 (SFT): Fine-tuned on the HPC-GPT instruction dataset (5,273 samples, 2 epochs)
Stage 2 (RL): HARGO reward-guided optimization with per-response adaptive weighting (3 epochs)
Hardware: Single RTX 3080 (16 GB)