README.md

metadata

thumbnail: https://github.com/rinnakk/japanese-pretrained-models/blob/master/rinna.png
license: llama3
base_model: rinna/llama-3-youko-8b
datasets:
  - mc4
  - wikipedia
  - EleutherAI/pile
  - oscar-corpus/colossal-oscar-1.0
  - cc100
language:
  - ja
  - en
inference: false
pipeline_tag: text-generation

QuantFactory/llama-3-youko-8b-GGUF

This is quantized version of rinna/llama-3-youko-8b created using llama.cpp

Model Description

Overview

We conduct continual pre-training of meta-llama/Meta-Llama-3-8B on 22B tokens from a mixture of Japanese and English datasets. The continual pre-training significantly improves the model's performance on Japanese tasks.

The name youko comes from the Japanese word 妖狐/ようこ/Youko, which is a kind of Japanese mythical creature (妖怪/ようかい/Youkai).

• Library

  The model was trained using code based on EleutherAI/gpt-neox.

• Model architecture

  A 32-layer, 4096-hidden-size transformer-based language model. Refer to the Llama 3 Model Card for architecture details.

• Training: Built with Meta Llama 3

  The model was initialized with the meta-llama/Meta-Llama-3-8B model and continually trained on around 22B tokens from a mixture of the following corpora

  • Japanese CC-100
  • Japanese C4
  • Japanese OSCAR
  • The Pile
  • Wikipedia
  • rinna curated Japanese dataset

• Contributors

  • Koh Mitsuda
  • Kei Sawada

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Benchmarking

Please refer to rinna's LM benchmark page.

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Tokenization

The model uses the original meta-llama/Meta-Llama-3-8B tokenizer.

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How to cite original model

@misc{rinna-llama-3-youko-8b, 
    title = {rinna/llama-3-youko-8b}, 
    author = {Mitsuda, Koh and Sawada, Kei},
    url = {https://huggingface.co/rinna/llama-3-youko-8b}, 
}

@inproceedings{sawada2024release,
    title = {Release of Pre-Trained Models for the {J}apanese Language},
    author = {Sawada, Kei and Zhao, Tianyu and Shing, Makoto and Mitsui, Kentaro and Kaga, Akio and Hono, Yukiya and Wakatsuki, Toshiaki and Mitsuda, Koh},
    booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
    month = {5},
    year = {2024},
    url = {https://arxiv.org/abs/2404.01657},
}

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References

@article{llama3modelcard,
    title={Llama 3 Model Card},
    author={AI@Meta},
    year={2024},
    url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
}

@software{gpt-neox-library,
    title = {{GPT-NeoX: Large Scale Autoregressive Language Modeling in PyTorch}},
    author = {Andonian, Alex and Anthony, Quentin and Biderman, Stella and Black, Sid and Gali, Preetham and Gao, Leo and Hallahan, Eric and Levy-Kramer, Josh and Leahy, Connor and Nestler, Lucas and Parker, Kip and Pieler, Michael and Purohit, Shivanshu and Songz, Tri and Phil, Wang and Weinbach, Samuel},
    doi = {10.5281/zenodo.5879544},
    month = {8},
    year = {2021},
    version = {0.0.1},
    url = {https://www.github.com/eleutherai/gpt-neox},
}

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License

Meta Llama 3 Community License