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atsuki-yamaguchi/gemma-2-9b-te-30K-lapt
gemma-2-9b-te-30K-lapt is a machine learning model from atsuki-yamaguchi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as gemma.
This model is built on top of Gemma2 9B adapted for Telugu using 30K target language sentences sampled from CC-100.
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Updated Dec 5, 2025
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From the Hugging Face model README
This model is built on top of Gemma2 9B adapted for Telugu using 30K target language sentences sampled from CC-100.
Use the code below to get started with the model.
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModelForCausalLM
model = AutoModelForCausalLM.from_pretrained(
"google/gemma-2-9b"
)
model = PeftModelForCausalLM.from_pretrained(
model,
"atsuki-yamaguchi/gemma-2-9b-te-30K-lapt"
)
model = model.merge_and_unload()
tokenizer = AutoTokenizer.from_pretrained(
"google/gemma-2-9b"
)
@article{yamaguchi-etal-2024-effectively,
title={How Can We Effectively Expand the Vocabulary of LLMs with 0.01GB of Target Language Text?},
author={Atsuki Yamaguchi and Aline Villavicencio and Nikolaos Aletras},
year={2024},
journal={ArXiv},
year={2024},
volume={abs/2406.11477},
url={https://arxiv.org/abs/2406.11477},
}