Qwen2.5 0.5B Instruct Gensyn Swarm Feathered Giant Ostrich

🚀 Qwen2.5-0.5B-Instruct-Gensyn-Swarm-feathered_giant_ostrich

本模型是基於Transformer架構的微調模型，在問答和文本生成任務上表現出色，為用戶提供更精準、高效的語言交互體驗。

🚀 快速開始

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="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-feathered_giant_ostrich", 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

• 微調優化：此模型是Gensyn/Qwen2.5-0.5B-Instruct的微調版本，經過優化以適應特定任務。
• 訓練框架：使用TRL進行訓練，提升了模型的性能和適應性。

📦 安裝指南

文檔未提供安裝步驟，暫不展示。

💻 使用示例

基礎用法

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="chinna6/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-feathered_giant_ostrich", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

高級用法

文檔未提供高級用法代碼示例，暫不展示。

📚 詳細文檔

訓練過程

本模型使用GRPO方法進行訓練，該方法在論文DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models中被提出。

框架版本

• TRL: 0.15.2
• Transformers: 4.48.2
• Pytorch: 2.5.1
• Datasets: 3.6.0
• Tokenizers: 0.21.1

引用信息

引用GRPO方法時，請使用以下格式：

@article{zhihong2024deepseekmath,
    title        = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
    author       = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
    year         = 2024,
    eprint       = {arXiv:2402.03300},
}

引用TRL框架時，請使用以下格式：

@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}}
}

📄 許可證

本模型遵循指定的許可證。具體許可證信息請參考 license 文件。