JEE 14B

🚀 jee_14b-20250408_071011

This model is a fine - tuned version of Qwen/Qwen2.5 - 14B - Instruct, trained using TRL, offering enhanced performance and capabilities.

🚀 Quick Start

This model is a fine-tuned version of Qwen/Qwen2.5-14B-Instruct. It has been trained using TRL.

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="kj42/jee_14b-20250408_071011", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

✨ Features

• Fine - tuned: Based on the Qwen/Qwen2.5-14B-Instruct model.
• Trained with TRL: Utilizes the TRL library for training.

📦 Installation

Since this model uses the transformers library, you can install it via the following command:

pip install transformers

📚 Documentation

Training procedure

This model was trained with SFT.

Framework versions

📄 License

This model is under the license license.

📄 Citations

Cite TRL as:

@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}}
}