Create README.md
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README.md
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---
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datasets:
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- hynky/czech_news_dataset_v2
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language:
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- cs
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library_name: transformers
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tags:
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- news
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- nlp
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- czech
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---
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- A model for predicting the source of news articles
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## Usage:
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```
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import re
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from transformers import pipeline
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from html import unescape
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from unicodedata import normalize
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re_multispace = re.compile(r"\s+")
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def normalize_text(text):
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if text == None:
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return None
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text = text.strip()
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text = text.replace("\n", " ")
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text = text.replace("\t", " ")
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text = text.replace("\r", " ")
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text = re_multispace.sub(" ", text)
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text = unescape(text)
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text = normalize("NFKC", text)
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return text
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model = pipeline(task="text-classification",
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model=f"hynky/Server", tokenizer="ufal/robeczech-base",
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truncation=True, max_length=512,
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top_k=5
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)
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def predict(article):
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article = normalize_text(article)
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predictions = model(article)
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predict("Dnes v noci bude pršet.")
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```
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