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README.md
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library_name: transformers
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---
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# Model Card for Model ID
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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---
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library_name: transformers
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language:
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- ru
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pipeline_tag: text-classification
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---
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# Model Card for Model ID
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## Uses
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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from transformers import TextClassificationPipeline,
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from transliterate import translit
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tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased")
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model = AutoModelForSequenceClassification.from_pretrained("CustomModel_Russia", num_labels=2)
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nlp = TextClassificationPipeline(model=model, tokenizer=tokenizer)
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#If the language of the text is different from English, use the 'translit' library.
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name = "Cтанислав"
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tran = translit(name, language_code='ru', reversed=True)
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result = nlp(tran)
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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