hajime9652
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README.md
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This model require Mecab and senetencepiece with XLNetTokenizer.
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See details https://qiita.com/mkt3/items/4d0ae36f3f212aee8002
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#### How to use
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```python
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import
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import subprocess
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from transformers import (
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pipeline,
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class XLNet():
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def __init__(self):
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path = (subprocess.Popen(cmd, stdout=subprocess.PIPE,
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shell=True).communicate()[0]).decode('utf-8')
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self.m = MeCab.Tagger(f"-Owakati -d {path}")
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self.gen_model = XLNetLMHeadModel.from_pretrained("hajime9652/xlnet-japanese")
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self.gen_tokenizer = XLNetTokenizer.from_pretrained("hajime9652/xlnet-japanese")
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This model require Mecab and senetencepiece with XLNetTokenizer.
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See details https://qiita.com/mkt3/items/4d0ae36f3f212aee8002
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This model uses NFKD as the normalization method for character encoding.
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Japanese muddle marks and semi-muddle marks will be lost.
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*日本語の濁点・半濁点がないモデルです*
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#### How to use
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```python
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from fugashi import Tagger
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from transformers import (
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pipeline,
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class XLNet():
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def __init__(self):
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self.m = Tagger('-Owakati')
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self.gen_model = XLNetLMHeadModel.from_pretrained("hajime9652/xlnet-japanese")
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self.gen_tokenizer = XLNetTokenizer.from_pretrained("hajime9652/xlnet-japanese")
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