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Ba2han / sft-lora-model-muon
Model's Last Updated: November 21 2025
text-generation
Introduction of sft-lora-model-muon
Model Details of sft-lora-model-muon
Model Card for sft-lora-model-muon
This model is a fine-tuned version of Ba2han/cpt-model-muon-3 . 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="Ba2han/sft-lora-model-muon", 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: 0.21.0
- Transformers: 4.56.1
- Pytorch: 2.8.0
- Datasets: 4.2.0
- Tokenizers: 0.22.0
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 Ba2han sft-lora-model-muon on huggingface.co
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More Information About sft-lora-model-muon huggingface.co Model
Url of sft-lora-model-muon
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Other API from Ba2han
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