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---
base_model:
- asas-ai/AceGPT-v2-8b-chat
datasets: HuggingFaceH4/Bespoke-Stratos-17k
library_name: transformers
model_name: AceGPT-v2-8b-chat-Open-R1-Distill
tags:
- generated_from_trainer
- open-r1
- trl
- sft
licence: license
---
# Model Card for AceGPT-v2-8b-chat-Open-R1-Distill
This model is a fine-tuned version of [asas-ai/AceGPT-v2-8b-chat](https://huggingface.co/asas-ai/AceGPT-v2-8b-chat) on the [HuggingFaceH4/Bespoke-Stratos-17k](https://huggingface.co/datasets/HuggingFaceH4/Bespoke-Stratos-17k) dataset.
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="asas-ai/AceGPT-v2-8b-chat-Open-R1-Distill", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
This model was trained with SFT.
### Framework versions
- TRL: 0.15.0.dev0
- Transformers: 4.49.0.dev0
- Pytorch: 2.5.1
- Datasets: 3.2.0
- Tokenizers: 0.21.0
## Citations
Cite open-r1 as:
```bibtex
@misc{open-r1,
title = {{Open R1: A fully open reproduction of DeepSeek-R1.}},
year = 2025,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/open-r1}}
}
```
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}}
}
``` |