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Additionally as recognized by the original dataset, the consonant voicing (連濁) of many words, especially numbers / number + counters, is incorrect. Such words' readings were fixed in the training data (i.e., 十匹: じゅうひき -> じっぴき).
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[Calvin-Xu/FLFL](https://huggingface.co/Calvin-Xu/FLFL/upload/main) is finetuned from [stockmark/gpt-neox-japanese-1.4b](https://huggingface.co/stockmark/gpt-neox-japanese-1.4b) and trained for slightly over one epoch on these data.
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Additionally as recognized by the original dataset, the consonant voicing (連濁) of many words, especially numbers / number + counters, is incorrect. Such words' readings were fixed in the training data (i.e., 十匹: じゅうひき -> じっぴき).
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[Calvin-Xu/FLFL](https://huggingface.co/Calvin-Xu/FLFL/upload/main) is finetuned from [stockmark/gpt-neox-japanese-1.4b](https://huggingface.co/stockmark/gpt-neox-japanese-1.4b) and trained for slightly over one epoch on these data.
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### FLFL Output Example
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<ruby><ruby>国境<rt>くにざかい</rt></ruby>の<ruby>長<rt>なが</rt></ruby>いトンネルを<ruby>抜<rt>ぬ</rt></ruby>けると<ruby>雪国<rt>ゆきぐに</rt></ruby>であった<|endoftext|>
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<ruby>鰤<rt>ぶり</rt></ruby>の<ruby>照<rt>て</rt></ruby>り<ruby>焼<rt>や</rt></ruby>き、<ruby>八宝菜<rt>はっぽうさい</rt></ruby>、ハンバーグ。<|endoftext|>
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<ruby>主菜<rt>しゅさい</rt></ruby><ruby>関連<rt>かんれん</rt></ruby>は、<ruby>見事<rt>みごと</rt></ruby>なまでの<ruby>和洋<rt>わよう</rt></ruby><ruby>中<rt>ちゅう</rt></ruby><ruby>折衷<rt>せっちゅう</rt></ruby>。<|endoftext|>
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<ruby>別<rt>べつ</rt></ruby>の<ruby>者<rt>もの</rt></ruby>の<ruby>目<rt>め</rt></ruby>を<ruby>通<rt>つう</rt></ruby>じて<ruby>歴史<rt>れきし</rt></ruby>を<ruby>垣間見<rt>かいまみ</rt></ruby>られるとは、<ruby>想像<rt>そうぞう</rt></ruby>を<ruby>超<rt>こ</rt></ruby>える<ruby>体験<rt>たいけん</rt></ruby>に<ruby>違<rt>ちが</rt></ruby>いない!<|endoftext|>
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<ruby>止<rt>と</rt></ruby>めるなら、その<ruby>大本<rt>おおもと</rt></ruby>を<ruby>根絶<rt>ねだ</rt></ruby>やしにしないと<ruby>効果<rt>こうか</rt></ruby>がないわ<|endoftext|>
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<ruby>不人気<rt>ふにんき</rt></ruby><ruby>銘柄<rt>かぶ</rt></ruby>でこれ<ruby>以上<rt>いじょう</rt></ruby><ruby>価値<rt>かち</rt></ruby>が<ruby>下<rt>さ</rt></ruby>がりようないから、ほとんど<ruby>底値<rt>そこね</rt></ruby>だ<|endoftext|>
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<ruby>時間<rt>じかん</rt></ruby>の<ruby>澱<rt>おり</rt></ruby>の<ruby>中<rt>なか</rt></ruby>に<ruby>沈殿<rt>ちんたい</rt></ruby>していたようだ。<|endoftext|>
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