Model Card for Qwen3-0.6B-turn-detection-en

This model is a fine-tuned version of Qwen/Qwen3-0.6B. It has been trained using TRL.

Quick start

from transformers import pipeline

system_prompt = "You are a speaking turn-ending identifier. Your task is to identify whether the user's speaking turn is complete or not. Respond with `end` if the user's turn is complete, or `continue` if it is not."
question = "I want to"

generator = pipeline("text-generation", model="None", device="cuda")
output = generator([{"role": "system", "content": system_prompt}, {"role": "user", "content": question}], max_new_tokens=1, return_full_text=False)[0]
print(output["generated_text"]) # "end" or "continue"

Training procedure

This model was trained with SFT.

Framework versions

• TRL: 0.21.0
• Transformers: 4.55.2
• Pytorch: 2.6.0
• Datasets: 3.6.0
• Tokenizers: 0.21.4

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 Gallou{\'e}dec},
    year         = 2020,
    journal      = {GitHub repository},
    publisher    = {GitHub},
    howpublished = {\url{https://github.com/huggingface/trl}}
}