# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/est-roberta")
model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/est-roberta")Quick Links
Usage
Load in transformers library with:
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/est-roberta")
model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/est-roberta")
Est-RoBERTa
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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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EMBEDDIA/est-roberta")