Qwen2.5-7B-my-lapt-madlad – AI Model by atsuki-yamaguchi | AlphaNeural AI

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atsuki-yamaguchi/
Qwen2.5-7B-my-lapt-madlad

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0

text-generation

allenai/MADLAD-400

Qwen/Qwen2.5-7B

autotrain_compatible

text-generation-inference

endpoints_compatible

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Qwen2.5 7B for Burmese: Continual pre-training only

This model is built on top of Qwen2.5 7B adapted for Burmese 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 Qwen2.5 7B.
Training: This model was continually pre-trained on 500M target language tokens sampled from MADLAD-400.

Model Description

Language: Burmese
License: Apache 2.0
Fine-tuned from model: Qwen/Qwen2.5-7B

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.

python

from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained(
    "atsuki-yamaguchi/Qwen2.5-7B-my-lapt-madlad"
)
tokenizer = AutoTokenizer.from_pretrained(
    "Qwen/Qwen2.5-7B"
)

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={}
}