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---
language:
- tr
tags:
- roberta
license: cc-by-nc-sa-4.0
datasets:
- oscar
---
# RoBERTa Turkish medium Character-level 16k (uncased)
Pretrained model on Turkish language using a masked language modeling (MLM) objective. The model is uncased.
The pretrained corpus is OSCAR's Turkish split, but it is further filtered and cleaned.
Model architecture is similar to bert-medium (8 layers, 8 heads, and 512 hidden size). Tokenization algorithm is Character-level, which means that text is split by individual characters. Vocabulary size is 16.7k.
## Note that this model does not include a tokenizer file, because it uses ByT5Tokenizer. The following code can be used for tokenization, example max length(1024) can be changed:
```
tokenizer = ByT5Tokenizer.from_pretrained("google/byt5-small")
tokenizer.mask_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][0]
tokenizer.cls_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][1]
tokenizer.bos_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][1]
tokenizer.sep_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][2]
tokenizer.eos_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][2]
tokenizer.pad_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][3]
tokenizer.unk_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][3]
tokenizer.model_max_length = 1024
```
The details can be found at this paper:
https://arxiv.org/...
### BibTeX entry and citation info
```bibtex
@article{}
```
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