Downloads · 30 days
25
27% of all-time downloads
RoyceLu/Qwen3-0.6B-OpenR1-SFT
Qwen3-0.6B-OpenR1-SFT is a text generation model from RoyceLu. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Qwen3-0.6B-OpenR1-SFT is a Qwen/Qwen3-0.6B-Base model fine-tuned with the Open-R1 SFT distillation recipe on the open-r1/Mixture-of-Thoughts dataset.
Downloads · 30 days
25
27% of all-time downloads
All-time downloads
93
Public
Parameters
596M
1.2 GB on disk
Likes
1
Public
Click a slice to open those files.
.safetensors1.2 GB · 98%
From the Hugging Face model README
Qwen3-0.6B-OpenR1-SFT is a Qwen/Qwen3-0.6B-Base model fine-tuned with the Open-R1 SFT distillation recipe on the open-r1/Mixture-of-Thoughts dataset.
Qwen/Qwen3-0.6B-BaseQwen3ForCausalLM32768This run used the Open-R1 supervised distillation recipe derived from recipes/OpenR1-Distill-7B/sft/config_distill.yaml with the base model overridden to Qwen/Qwen3-0.6B-Base and the Hub target set to RoyceLu/Qwen3-0.6B-OpenR1-SFT.
Key settings:
open-r1/Mixture-of-Thoughts (all config)5327684e-528bf16flash_attention_2open-r1/Mixture-of-Thoughts349,3171 x node, 8 x NVIDIA H100 80GB168,141.7s (1d 22h 42m 22s)13,6500.6757Benchmarks were evaluated with lighteval + vLLM on single H100 GPUs. For all runs below, both baseline and fine-tuned models used the same inference settings:
max_model_length=8192temperature=0.6top_p=0.95use_chat_template=truemax_new_tokens=2048| Benchmark | Qwen/Qwen3-0.6B-Base | Qwen3-0.6B-OpenR1-SFT | Delta (pp) |
|---|---|---|---|
AIME 2024 (LightEval pass@1, 64 samples) | 0.05% | 0.10% | +0.05 pp |
MATH-500 (LightEval pass@1, 4 samples) | 36.85% | 35.40% | -1.45 pp |
GPQA Diamond (LightEval pass@1, 8 samples) | 25.44% | 26.96% | +1.52 pp |
LiveCodeBench (LightEval pass@1, 16 samples) | 0.0933% | 1.6325% | +1.5392 pp |
max_new_tokens=4096| Benchmark | Qwen/Qwen3-0.6B-Base | Qwen3-0.6B-OpenR1-SFT | Delta (pp) |
|---|---|---|---|
AIME 2024 (LightEval pass@1, 64 samples) | 0.68% | 1.41% | +0.73 pp |
MATH-500 (LightEval pass@1, 4 samples) | 36.80% | 41.95% | +5.15 pp |
GPQA Diamond (LightEval pass@1, 8 samples) | 24.87% | 26.77% | +1.89 pp |
LiveCodeBench (LightEval pass@1, 16 samples) | 0.0466% | 0.0231% | -0.0235 pp |
from transformers import pipeline
pipe = pipeline(
"text-generation",
model="RoyceLu/Qwen3-0.6B-OpenR1-SFT",
device="cuda",
)
messages = [{"role": "user", "content": "Solve x^2 - 5x + 6 = 0."}]
output = pipe(messages, max_new_tokens=512, return_full_text=False)
print(output[0]["generated_text"])
If you use this model in research, evaluations, or derivative model releases, please cite this model together with Qwen3 and Open-R1.
@misc{lu2026qwen3openr1sft,
author = {Royce Lu},
title = {Qwen3-0.6B-OpenR1-SFT},
year = {2026},
howpublished = {Hugging Face model repository},
note = {Fine-tuned from Qwen/Qwen3-0.6B-Base using the Open-R1 supervised distillation recipe}
}