base_model, library_name, model_name, tags, licence
base_model library_name model_name tags licence
Qwen/Qwen3-0.6B transformers distilled-model-v1
generated_from_trainer
sft
trl
license

Model Card for distilled-model-v1

This model is a fine-tuned version of Qwen/Qwen3-0.6B. 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="Satyach/distilled-model-v1", 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: 0.19.1
  • Transformers: 4.53.0
  • Pytorch: 2.7.1
  • Datasets: 4.0.0
  • 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}}
}
Description
Model synced from source: Satyach/distilled-model-v1
Readme 2 MiB
Languages
Python 72.7%
Jinja 27.3%