---
base_model: Qwen/Qwen2.5-Math-7B-Instruct
library_name: transformers
model_name: qwen-prm-7b-soft-labels
datasets:
- axolotl-ai-co/Math-Shepherd
- axolotl-ai-co/prm800k_phase_1
- axolotl-ai-co/prm800k_phase_2
tags:
- generated_from_trainer
- axolotl
- trl
- prm
licence: license
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
# Model Card for qwen-prm-7b-soft-labels
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct).
It has been trained using [Axolotl](https://github.com/axolotl-ai-cloud/axolotl) with [TRL](https://github.com/huggingface/trl).
## Quick start
```python
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="axolotl-ai-co/qwen-prm-7b-soft-labels", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
[
](https://wandb.ai/axolotl-ai/qwen-prm-7b/runs/tqfwuxrc)
This model was trained with PRM.
### Framework versions
- TRL: 0.13.0
- Transformers: 4.48.1
- Pytorch: 2.5.1+cu124
- Datasets: 3.2.0
- Tokenizers: 0.21.0
## Citations
Cite PRM as:
```bibtex
@article{uesato2022solving,
title = {Solving Math Word Problems With Process- and Outcome-Based Feedback},
author = {Uesato, Jonathan and Kushman, Nate and Kumar, Ramana and Song, Francis and Siegel, Noah and Wang, Lisa and Creswell, Antonia and Irving, Geoffrey and Higgins, Irina},
year = 2022,
journal = {arXiv preprint arXiv:2211.14275}
}
```
Cite TRL as:
```bibtex
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
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},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
```