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README.md
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@@ -39,6 +39,7 @@ The resulting model has 356M parameters, a vocabulary of 50.670 tokens, and a si
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```python
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from transformers import RobertaTokenizerFast, RobertaForMaskedLM
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tokenizer = RobertaTokenizerFast.from_pretrained("osiria/roberta-large-italian")
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model = RobertaForMaskedLM.from_pretrained("osiria/roberta-large-italian")
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```python
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from transformers import RobertaTokenizerFast, RobertaForMaskedLM
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from transformers import pipeline
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tokenizer = RobertaTokenizerFast.from_pretrained("osiria/roberta-large-italian")
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model = RobertaForMaskedLM.from_pretrained("osiria/roberta-large-italian")
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