---
library_name: transformers
model_name: prm
tags:
- generated_from_trainer
- reward-trainer
- trl
licence: license
---

# Model Card for prm

This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).

## Quick start

```python
from transformers import pipeline

text = "The capital of France is Paris."
rewarder = pipeline(model="None", device="cuda")
output = rewarder(text)[0]
print(output["score"])
```

## Training procedure

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/lilin22/zhaowang/runs/7233254701.72867-f9dda944-4408) 


This model was trained with Reward.

### Framework versions

- TRL: 0.26.2
- Transformers: 4.57.3
- Pytorch: 2.8.0
- Datasets: 4.4.2
- Tokenizers: 0.22.1

## Citations



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 Gallou{\'e}dec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}
```