rinna/llama-3-youko-8b
Llama 3 Youko 8B (rinna/llama-3-youko-8b)
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
- Release date
May 1, 2024
Benchmarking
Please refer to rinna's LM benchmark page (Sheet 20240507).
How to use the model
~~~~python import transformers import torch
modelid = "rinna/llama-3-youko-8b" pipeline = transformers.pipeline( "text-generation", model=modelid, modelkwargs={"torchdtype": torch.bfloat16}, devicemap="auto" ) output = pipeline( "西田幾多郎は、", maxnewtokens=256, dosample=True ) print(output[0]["generated_text"]) ~~~~
Tokenization
The model uses the original meta-llama/Meta-Llama-3-8B tokenizer.
How to cite
@misc{rinna-llama-3-youko-8b,
title = {rinna/llama-3-youko-8b},
author = {Mitsuda, Koh and Chen, Xinqi and Wakatsuki, Toshiaki 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},
pages = {13898--13905},
url = {https://aclanthology.org/2024.lrec-main.1213},
note = {\url{https://arxiv.org/abs/2404.01657}}
}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}-{N}eo{X}: Large Scale Autoregressive Language Modeling in {P}y{T}orch},
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}
}