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KAERI-MLP/AtomicGPT-gemma2-9B
AtomicGPT-gemma2-9B is a machine learning model from KAERI-MLP. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as gemma.
AtomicGPT is a large language model (LLM) specialized in the nuclear engineering domain, developed at the Korea Atomic Energy Research Institute (KAERI). Based on Gemma2-9B, AtomicGPT deeply understands various nuclea…
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From the Hugging Face model README
AtomicGPT is a large language model (LLM) specialized in the nuclear engineering domain, developed at the Korea Atomic Energy Research Institute (KAERI). Based on Gemma2-9B, AtomicGPT deeply understands various nuclear technologies, theories, and terminology, including reactor design, radiation shielding, the nuclear fuel cycle, and nuclear safety and regulations. With this expertise, AtomicGPT delivers precise answers to technical and specialized questions in the nuclear domain.
| Base Model | google/gemma-2-9b |
| Training | Continual Pre-training (CPT) + Instruction Tuning (IT) |
| Domain | Nuclear Engineering |
| Languages | Korean, English |
| License | Gemma |
| Model | Multiple-Choice (EM) | Short-Answer (F1, %) | Descriptive (1–10) |
|---|---|---|---|
| Gemma2-9B (base) | 23 | 12.16 | 3.65 |
| AtomicGPT-Gemma2-9B (ours) | 40 | 19.72 | 4.67 |
| GPT-4 | 48 | 31.29 | 7.70 |
All evaluations were conducted under a zero-shot setting.
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "KAERI-MLP/AtomicGPT-Gemma2-9B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
device_map="auto",
)
model.eval()
input_text = "Query about Nuclear (Atomic Energy)"
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**input_ids, max_new_tokens=1024)
print(tokenizer.decode(outputs[0]))
If you use this model in your research, please cite:
@article{atomicgpt2026,
title={AtomicGPT: A Domain-Adapted Large Language Model for Secure On-Premise Applications in Nuclear Engineering},
journal={Nuclear Engineering and Technology},
year={2026}
}
Developed by the MLP (Multimodal Language Processing) team at the Korea Atomic Energy Research Institute (KAERI).