rinna/llama-3-youko-70b-gptq is the quantized model for
rinna/llama-3-youko-70b
using
AutoGPTQ
. The quantized version is 4x smaller than the original model and thus requires less memory and provides faster inference.
@misc{rinna-llama-3-youko-70b-gptq,
title = {rinna/llama-3-youko-70b-gptq},
author = {Wakatsuki, Toshiaki and Mitsuda, Koh and Chen, Xinqi and Sawada, Kei},
url = {https://huggingface.co/rinna/llama-3-youko-70b-gptq}
}
@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}
}
@article{frantar2022gptq,
title = {{GPTQ}: Accurate Post-training Compression for Generative Pretrained Transformers},
author = {Frantar, Elias and Ashkboos, Saleh and Hoefler, Torsten and Alistarh, Dan},
year = {2022},
url = {https://arxiv.org/abs/2210.17323}
}
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