Qwen2.5 1.5B S1k 1.1

🚀 Qwen2.5-1.5B-s1k-1.1

该模型是基于Qwen/Qwen2.5-1.5B-Instruct微调而来，使用TRL进行训练，为文本生成任务提供了强大的支持。

🚀 快速开始

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="rvindra/Qwen2.5-1.5B-s1k-1.1", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

✨ 主要特性

• 该模型是Qwen/Qwen2.5-1.5B-Instruct的微调版本。
• 使用TRL进行训练。

📦 安装指南

文档未提及安装步骤，故跳过该章节。

📚 详细文档

训练过程

此模型使用SFT进行训练。

框架版本

• TRL: 0.16.1
• Transformers: 4.50.3
• Pytorch: 2.5.1
• Datasets: 3.0.2
• Tokenizers: 0.21.0

📄 许可证

该模型遵循 license 许可证。

📚 引用信息

引用TRL时请使用以下格式：

@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}}
}