---
library_name: transformers
tags: []
---

# Zerpal-rubert-tiny2-v2

## How to use

You can use this model directly with a pipeline for masked language modeling:

```py
from transformers import pipeline

unmasker = pipeline('fill-mask', model='udmurtNLP/zerpal-rubert-tiny2-v2', tokenizer='udmurtNLP/zerpal-rubert-tiny2-tokenizer-v2')

unmasker("Ӟечбур! Мынам нимы [MASK].")
```

Here is how to use this model to get the features of a given text in PyTorch:
```py
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained('udmurtNLP/zerpal-rubert-tiny2-tokenizer-v2')
model = AutoModelForMaskedLM.from_pretrained("udmurtNLP/zerpal-rubert-tiny2-v2")
text = "Яратон, яратон, мар меда сыӵе тон?"
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)
```