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Sponsored by
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lewtun / SmolLM2-360M-OpenMathReasoning
Model's Last Updated: May 11 2026
text-generation
Introduction of SmolLM2-360M-OpenMathReasoning
Model Details of SmolLM2-360M-OpenMathReasoning
Model Card for SmolLM2-360M-OpenMathReasoning
This model is a fine-tuned version of HuggingFaceTB/SmolLM2-360M-Instruct . It has been trained using TRL .
Quick start
from transformers import pipeline
question = "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?"
generator = pipeline("text-generation", model="lewtun/SmolLM2-360M-OpenMathReasoning", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
Training procedure
This model was trained with SFT.
Framework versions
- TRL: 1.4.0
- Transformers: 5.8.0
- Pytorch: 2.11.0
- Datasets: 4.8.5
- Tokenizers: 0.22.2
Citations
Cite TRL as:
@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
license = {Apache-2.0},
url = {https://github.com/huggingface/trl},
year = {2020}
}
Runs of lewtun SmolLM2-360M-OpenMathReasoning on huggingface.co
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More Information About SmolLM2-360M-OpenMathReasoning huggingface.co Model
Url of SmolLM2-360M-OpenMathReasoning
SmolLM2-360M-OpenMathReasoning huggingface.co Url
Provider of SmolLM2-360M-OpenMathReasoning huggingface.co
Other API from lewtun
Updated:April 29 2026
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