qwen2.5-3B-Instruct-tool-call-en-mixed-when2call-v3

⚠️ Warning

This model was fine-tuned for experimental purposes, as part of an investigation into reducing over-triggered tool calls (i.e., getting the model to correctly abstain when no tool is relevant).

nvidia/When2Call (train_sft) was included in training to improve this behavior. However, this had an unintended side effect: the model's core tool-calling ability degraded significantly. It now frequently asks the user for clarification/input even for simple, complete, unambiguous tool-call requests where all required parameters are already provided.

Do not use this model in production or for tool-calling tasks. It is kept public only as a record of this experiment (see BFCL eval results above — simple_python_acc and multiple_acc collapsed while irrelevance_acc hit ceiling, indicating over-correction rather than genuine improvement).

Model Card for qwen2.5-3B-Instruct-tool-call-en-mixed-when2call-v3

This model is a fine-tuned version of Qwen/Qwen2.5-3B-Instruct. It has been trained using TRL.

Quick start

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="canbingol/qwen2.5-3B-Instruct-tool-call-en-mixed-when2call-v3", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

This model was trained with SFT.

Framework versions

• TRL: 1.10.0
• Transformers: 5.13.1
• Pytorch: 2.11.0+cu128
• Datasets: 5.0.1
• Tokenizers: 0.22.2

Citations

Cite TRL as:

@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}