KwabsHug commited on
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51966ed
1 Parent(s): a8211e6

Update app.py

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Files changed (1) hide show
  1. app.py +19 -19
app.py CHANGED
@@ -20,25 +20,25 @@ import textwrap
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  import pandas as pd
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  #Uncomment these for Huggingface
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- #nltk.download('maxent_ne_chunker') #Chunker
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- #nltk.download('stopwords') #Stop Words List (Mainly Roman Languages)
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- #nltk.download('words') #200 000+ Alphabetical order list
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- #nltk.download('punkt') #Tokenizer
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- #nltk.download('verbnet') #For Description of Verbs
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- #nltk.download('omw')
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- #nltk.download('omw-1.4') #Multilingual Wordnet
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- #nltk.download('wordnet') #For Definitions, Antonyms and Synonyms
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- #nltk.download('shakespeare')
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- #nltk.download('dolch') #Sight words
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- #nltk.download('names') #People Names NER
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- #nltk.download('gazetteers') #Location NER
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- #nltk.download('opinion_lexicon') #Sentiment words
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- #nltk.download('averaged_perceptron_tagger') #Parts of Speech Tagging
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-
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- #spacy.cli.download("en_core_web_sm")
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- #spacy.cli.download('ko_core_news_sm')
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- #spacy.cli.download('ja_core_news_sm')
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- #spacy.cli.download('zh_core_web_sm')
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  nlp = spacy.load('en_core_web_sm')
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  translator = Translator()
 
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  import pandas as pd
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  #Uncomment these for Huggingface
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+ nltk.download('maxent_ne_chunker') #Chunker
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+ nltk.download('stopwords') #Stop Words List (Mainly Roman Languages)
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+ nltk.download('words') #200 000+ Alphabetical order list
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+ nltk.download('punkt') #Tokenizer
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+ nltk.download('verbnet') #For Description of Verbs
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+ nltk.download('omw')
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+ nltk.download('omw-1.4') #Multilingual Wordnet
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+ nltk.download('wordnet') #For Definitions, Antonyms and Synonyms
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+ nltk.download('shakespeare')
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+ nltk.download('dolch') #Sight words
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+ nltk.download('names') #People Names NER
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+ nltk.download('gazetteers') #Location NER
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+ nltk.download('opinion_lexicon') #Sentiment words
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+ nltk.download('averaged_perceptron_tagger') #Parts of Speech Tagging
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+
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+ spacy.cli.download("en_core_web_sm")
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+ spacy.cli.download('ko_core_news_sm')
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+ spacy.cli.download('ja_core_news_sm')
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+ spacy.cli.download('zh_core_web_sm')
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  nlp = spacy.load('en_core_web_sm')
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  translator = Translator()