---
license: apache-2.0
datasets:
- kz-transformers/multidomain-kazakh-dataset
language:
- kk
pipeline_tag: fill-mask
library_name: transformers
---
# Kaz-RoBERTa (base-sized model) 

## Model description



## Usage

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

```python
>>> from transformers import pipeline
>>> unmasker = pipeline('fill-mask', model='kz-transformers/kaz-roberta-conversational')
>>> unmasker("Hello I'm a <mask> model.")



Here is how to use this model to get the features of a given text in PyTorch:

```python
from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("kz-transformers/kaz-roberta-conversational")
model = AutoModelForMaskedLM.from_pretrained("kz-transformers/kaz-roberta-conversational")

# prepare input
text = "Replace me by any text you'd like."
encoded_input = tokenizer(text, return_tensors='pt')

# forward pass
output = model(**encoded_input)
```

### BibTeX entry and citation info