llama-3-youko-8b-gptq

Llama 3 Youko 8B GPTQ (rinna/llama-3-youko-8b-gptq)

Overview

rinna/llama-3-youko-8b-gptq is the quantized model for rinna/llama-3-youko-8b using AutoGPTQ. The quantized version is 4x smaller than the original model and thus requires less memory and provides faster inference.

• Training: Built with Meta Llama 3

  See rinna/llama-3-youko-8b for details about model architecture and data.

• Contributors

  • Toshiaki Wakatsuki
  • Koh Mitsuda
  • Xinqi Chen
  • Kei Sawada

• Release date

  July 25, 2024

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Benchmarking

Please refer to rinna's LM benchmark page (Sheet 20240725).

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How to use the model

import transformers
import torch

model_id = "rinna/llama-3-youko-8b-gptq"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    device_map="auto"
)
output = pipeline(
    "西田幾多郎は、",
    max_new_tokens=256,
    do_sample=True
)
print(output[0]["generated_text"])

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Tokenization

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

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How to cite

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

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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}
}

@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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License

Meta Llama 3 Community License