base_model, datasets, library_name, model_name, tags, licence

base_model	datasets	library_name	model_name	tags	licence
Qwen/Qwen2.5-7B-Instruct	Neelectric/OpenR1-Math-220k_all_Llama3_4096toks	transformers	Qwen2.5-7B-Instruct_SFT_mathv00.02	generated_from_trainer sft trl open-r1	license

Model Card for Qwen2.5-7B-Instruct_SFT_mathv00.02

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset. 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="Neelectric/Qwen2.5-7B-Instruct_SFT_mathv00.02", 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: 1.1.0.dev0
• Transformers: 4.57.6
• Pytorch: 2.7.1
• 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}
}