Llama-3.1-8B-Instruct-am-lapt-madlad/README.md

---

license: llama3.1 datasets:

• allenai/MADLAD-400 language:
• am base_model:
• meta-llama/Llama-3.1-8B-Instruct library_name: transformers

---

Llama 3.1 8B Instruct for Amharic: Continual pre-training only

This model is built on top of Llama 3.1 8B Instruct adapted for Amharic using 500M target language tokens sampled from MADLAD-400.

Model Details

• Vocabulary: This model has no additional target vocabulary. It retains the original vocabulary of Llama 3.1 8B Instruct.
• Training: This model was continually pre-trained on 500M target language tokens sampled from MADLAD-400.

Model Description

• Language: Amharic
• License: Llama 3.1 Community License Agreement
• Fine-tuned from model: meta-llama/Llama-3.1-8B-Instruct

Model Sources

• Repository: https://github.com/gucci-j/chat-cve
• Paper: https://arxiv.org/abs/2412.11704

How to Get Started with the Model

Use the code below to get started with the model.

from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained(
    "atsuki-yamaguchi/Llama-3.1-8B-Instruct-am-lapt-madlad"
)
tokenizer = AutoTokenizer.from_pretrained(
    "meta-llama/Llama-3.1-8B-Instruct"
)

Citation

@article{yamaguchi2025adapting,
      title={Adapting Chat Language Models Using Only Target Unlabeled Language Data}, 
      author={Atsuki Yamaguchi and Terufumi Morishita and Aline Villavicencio and Nikolaos Aletras},
      journal={Transactions on Machine Learning Research},
      issn={2835-8856},
      year={2025},
      url={https://openreview.net/forum?id=6IdoIKowfe},
      note={}
}