Model Card for Tars

This model is a fine-tuned version of Qwen/Qwen2.5-Math-7B-Instruct on the mlfoundations-dev/putnam_bench_r1 dataset. It has been trained using TRL.

Quick start

from transformers import pipeline

text = "The capital of France is Paris."
rewarder = pipeline(model="dkjo8/Tars", device="cuda")
output = rewarder(text)[0]
print(output["score"])

Training procedure

This model was trained with Reward.

Framework versions

• TRL: 1.5.1
• Transformers: 5.9.0
• Pytorch: 2.12.0
• 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}
}