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Sponsored by
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sghosts / gemma3_4b_bilsemqa_r16_alpha32
Model's Last Updated: December 31 2025
text-generation
Introduction of gemma3_4b_bilsemqa_r16_alpha32
Model Details of gemma3_4b_bilsemqa_r16_alpha32
Model Card for gemma3_4b_bilsemqa_r16_alpha32
This model is a fine-tuned version of google/gemma-3-4b-it . 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="None", 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
- PEFT 0.18.0
- TRL: 0.26.1
- Transformers: 4.57.3
- Pytorch: 2.9.1
- Datasets: 4.4.1
- Tokenizers: 0.22.1
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 sghosts gemma3_4b_bilsemqa_r16_alpha32 on huggingface.co
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More Information About gemma3_4b_bilsemqa_r16_alpha32 huggingface.co Model
Url of gemma3_4b_bilsemqa_r16_alpha32
gemma3_4b_bilsemqa_r16_alpha32 huggingface.co Url
Provider of gemma3_4b_bilsemqa_r16_alpha32 huggingface.co
Other API from sghosts
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