Load in transformers library with:
from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/sloberta") model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/sloberta")
SloBERTa model is a monolingual Slovene BERT-like model. It is closely related to French Camembert model https://camembert-model.fr/. The corpora used for training the model have 3.47 billion tokens in total. The subword vocabulary contains 32,000 tokens. The scripts and programs used for data preparation and training the model are available on https://github.com/clarinsi/Slovene-BERT-Tool
SloBERTa was trained for 200,000 iterations or about 98 epochs.
The following corpora were used for training the model:
- Gigafida 2.0
- Kas 1.0
- Janes 1.0 (only Janes-news, Janes-forum, Janes-blog, Janes-wiki subcorpora)
- Slovenian parliamentary corpus siParl 2.0
Select AutoNLP in the “Train” menu to fine-tune this model automatically.
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