metadata
license: llama2
language:
- ar
base_model: meta-llama/Llama-2-7b-hf
library_name: transformers
Llama2 7B for Arabic: No vocabulary adaptation
This model is built on top of Llama2 7B adapted for Arabic 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 Llama2 7B.
Model Description
- Language: Arabic
- License: Llama 2 Community License Agreement
- Fine-tuned from model: meta-llama/Llama-2-7b-hf
Model Sources
- Repository: https://github.com/gucci-j/lowres-cve
- Paper: https://arxiv.org/abs/2406.11477
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(
"meta-llama/Llama-2-7b-hf"
)
model = PeftModelForCausalLM.from_pretrained(
model,
"atsuki-yamaguchi/Llama-2-7b-hf-ar-30K-lapt"
)
model = model.merge_and_unload()
tokenizer = AutoTokenizer.from_pretrained(
"meta-llama/Llama-2-7b-hf"
)
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},
}