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Sponsored by
APIMart
ncgc / qwen-3.0B-sft
Model's Last Updated: July 25 2025
text-generation
Introduction of qwen-3.0B-sft
Model Details of qwen-3.0B-sft
Model Card for qwen-3.0B-sft
This model is a fine-tuned version of Qwen/Qwen2.5-3B . 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="ncgc/qwen-3.0B-sft", 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: 4.53.3
- Pytorch: 2.8.0a0+gite2f9759
- Datasets: 3.6.0
- 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 ncgc qwen-3.0B-sft on huggingface.co
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More Information About qwen-3.0B-sft huggingface.co Model
Url of qwen-3.0B-sft
qwen-3.0B-sft huggingface.co Url
Provider of qwen-3.0B-sft huggingface.co
Other API from ncgc
Updated:August 19 2025
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