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Baguettotron-SFT-Tulu3-deco…/README.md
ModelHub XC 3ca893466d 初始化项目,由ModelHub XC社区提供模型
Model: ali-elganzory/Baguettotron-SFT-Tulu3-decontaminated
Source: Original Platform
2026-04-13 08:58:58 +08:00

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---
base_model: PleIAs/Baguettotron
library_name: transformers
tags:
- generated_from_trainer
- trl
- sft
licence: license
---
# Model Card for None
This model is a fine-tuned version of [PleIAs/Baguettotron](https://huggingface.co/PleIAs/Baguettotron).
It has been trained using [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="None", 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: 0.27.1
- Transformers: 4.57.6
- Pytorch: 2.6.0+cu126
- Datasets: 4.8.4
- Tokenizers: 0.22.2
## 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}}
}
```