This model is a fine-tuned version of
Qwen/Qwen3-4B
.
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="qgallouedec/trainer_output", 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: 0.20.0.dev0
Transformers: 4.54.0.dev0
Pytorch: 2.7.1
Datasets: 4.0.0
Tokenizers: 0.21.2
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}}
}
Runs of qgallouedec trainer_output on huggingface.co
16
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
16
30-day runs
More Information About trainer_output huggingface.co Model
trainer_output huggingface.co
trainer_output huggingface.co is an AI model on huggingface.co that provides trainer_output's model effect (), which can be used instantly with this qgallouedec trainer_output model. huggingface.co supports a free trial of the trainer_output model, and also provides paid use of the trainer_output. Support call trainer_output model through api, including Node.js, Python, http.
trainer_output huggingface.co is an online trial and call api platform, which integrates trainer_output's modeling effects, including api services, and provides a free online trial of trainer_output, you can try trainer_output online for free by clicking the link below.
qgallouedec trainer_output online free url in huggingface.co:
trainer_output is an open source model from GitHub that offers a free installation service, and any user can find trainer_output on GitHub to install. At the same time, huggingface.co provides the effect of trainer_output install, users can directly use trainer_output installed effect in huggingface.co for debugging and trial. It also supports api for free installation.