Gemma2 9B for Telugu: No vocabulary adaptation

This model is built on top of Gemma2 9B adapted for Telugu using 30K target language sentences sampled from CC-100.

Model Details

  • Vocabulary: This model has no additional target vocabulary. It retains the original vocabulary of Gemma2 9B.

Model Description

  • Language: Telugu
  • License: Gemma Terms of Use
  • Fine-tuned from model: google/gemma-2-9b

Model Sources

How to Get Started with the Model

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"
)

Citation

@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}, 
}
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