Add tokenizer.json

#3
by Narsil HF staff - opened
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  1. README.md +0 -18
README.md CHANGED
@@ -62,23 +62,5 @@ Here are a few samples generated with and without the toy prefix weights, respec
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  # Inference with FasterTransformer
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  After version 5.1, [NVIDIA FasterTransformer](https://github.com/NVIDIA/FasterTransformer) now supports both inference for GPT-NeoX and a variety of soft prompts (including prefix-tuning). The released pretrained model and prefix weights in this repo have been verified to work with FasterTransformer 5.1.
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- # How to cite
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- ~~~
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- @misc{rinna-japanese-gpt-neox-small,
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- title = {rinna/japanese-gpt-neox-small},
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- author = {Zhao, Tianyu and Sawada, Kei}
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- url = {https://huggingface.co/rinna/japanese-gpt-neox-small},
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- }
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-
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- @inproceedings{sawada2024release,
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- title = {Release of Pre-Trained Models for the {J}apanese Language},
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- author = {Sawada, Kei and Zhao, Tianyu and Shing, Makoto and Mitsui, Kentaro and Kaga, Akio and Hono, Yukiya and Wakatsuki, Toshiaki and Mitsuda, Koh},
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- booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
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- month = {5},
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- year = {2024},
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- url = {https://arxiv.org/abs/2404.01657},
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- }
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- ~~~
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-
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  # Licenese
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  [The MIT license](https://opensource.org/licenses/MIT)
 
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  # Inference with FasterTransformer
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  After version 5.1, [NVIDIA FasterTransformer](https://github.com/NVIDIA/FasterTransformer) now supports both inference for GPT-NeoX and a variety of soft prompts (including prefix-tuning). The released pretrained model and prefix weights in this repo have been verified to work with FasterTransformer 5.1.
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  # Licenese
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  [The MIT license](https://opensource.org/licenses/MIT)