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--- |
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library_name: transformers |
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language: |
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- udm |
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--- |
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# Zerpal-Glot500 |
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## How to use |
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You can use this model directly with a pipeline for masked language modeling: |
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```py |
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from transformers import pipeline |
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unmasker = pipeline('fill-mask', model='udmurtNLP/zerpal-glot500', tokenizer='cis-lmu/glot500-base') |
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unmasker("Ӟечбур! Мынам нимы <mask>.") |
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``` |
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Here is how to use this model to get the features of a given text in PyTorch: |
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```py |
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from transformers import AutoTokenizer, AutoModelForMaskedLM |
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tokenizer = AutoTokenizer.from_pretrained('cis-lmu/glot500-base') |
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model = AutoModelForMaskedLM.from_pretrained("udmurtNLP/zerpal-glot500") |
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text = "Яратон, яратон, мар меда сыӵе тон?" |
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encoded_input = tokenizer(text, return_tensors='pt') |
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output = model(**encoded_input) |
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``` |
