Instructions to use Makhmud/Kun_uz_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Makhmud/Kun_uz_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Makhmud/Kun_uz_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Makhmud/Kun_uz_classification") model = AutoModelForSequenceClassification.from_pretrained("Makhmud/Kun_uz_classification") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: openrail
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license: openrail
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## NLP Classification task in Uzbek language!
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I used data from the kun.uz website for this task(https://lnkd.in/dZcjU8hX).
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This dataset contains more than 170000 news and these news are divided into 7 categories. This dataset has a imbalance problem so I have selected 4 categories("Jamiyat", "O'zbekiston", "Jahon" and "Fan va Texnika" ).
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Program code: https://lnkd.in/dqraUG2Q
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Model for testing: https://lnkd.in/dqjB7aJs
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You can select and test a small part of news from one of the categories mentioned above from the kun.uz website.
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