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| Benchmark | GemmaCoder-12B | Gemma3-12B-it |
|---|---|---|
| Winogrande | 63.9% | 63.5% |
| MMLU | 61.0% | 69.5% |
| HellaSwag | 54.0% | 53.5% |
| LiveCodeBench | 32.9% | 21.9% |
1from transformers import pipeline
2
3question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
4generator = pipeline("text-generation", model="burtenshaw/gemma-3-12b-it-codeforces-SFT", device="cuda")
5output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
6print(output["generated_text"])
1@misc{vonwerra2022trl,
2 title = {{TRL: Transformer Reinforcement Learning}},
3 author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
4 year = 2020,
5 journal = {GitHub repository},
6 publisher = {GitHub},
7 howpublished = {\url{https://github.com/huggingface/trl}}
8}