Load in transformers library with:
from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/est-roberta", use_fast=False) model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/est-roberta")
NOTE: it is currently critically important to add
use_fast=False parameter to tokenizer if using transformers version 4+ (prior versions have
use_fast=False as default) By default it attempts to load a fast tokenizer, which might work (ie. not result in an error), but not correctly, as there is no current support for fast tokenizers for Camembert-based models.
Est-RoBERTa model is a monolingual Estonian BERT-like model. It is closely related to French Camembert model https://camembert-model.fr/. The Estonian corpora used for training the model have 2.51 billion tokens in total. The subword vocabulary contains 40,000 tokens.
Est-RoBERTa was trained for 40 epochs.
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