pytorch camembert masked-lm et transformers license:cc-by-sa-4.0 fill-mask
.gitattributes README.md config.json dict.txt pytorch_model.bin sentencepiece.bpe.model
---
language: 
- et

license: cc-by-sa-4.0
---
# Usage
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
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.

