This is a model for trainable transliteration from Latin (English but not only) to Russian Cyrillic
How to use:
import torch
from transformers import BertForMaskedLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("cointegrated/bert-char-ctc-en-ru-translit-v0", trust_remote_code=True)
model = BertForMaskedLM.from_pretrained("cointegrated/bert-char-ctc-en-ru-translit-v0")
text = 'Hello world! My name is David Dale, and yours is Schwarzenegger?'
with torch.inference_mode():
batch = tokenizer(text, return_tensors='pt', spaces=1, padding=True).to(model.device)
logits = torch.log_softmax(model(**batch).logits, axis=-1)
print(tokenizer.decode(logits[0].argmax(-1), skip_special_tokens=True))
# хэло Уорлд май нэйм из дэвид дэйл энд ёрз из скУорзэнэгжэр
The argument spaces could be from 0 to 4, and it affects the results; a recommended value is 2.
Why use:
Just for fun
To augment your training data, if for some reason you want to make it robust to script changes
Model Details
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