README.md

---
language:
- "bo"
tags:
- "tibetan"
- "masked-lm"
license: "cc-by-sa-4.0"
pipeline_tag: "fill-mask"
mask_token: "[MASK]"
datasets:
- UTibetNLP/tibetan_news_classification
---

# roberta-base-tibetan

## Model Description

This is a RoBERTa model pre-trained on Tibetan texts. NVIDIA A100-SXM4-40GB took 40 hours 44 minutes for training. You can fine-tune `roberta-base-tibetan` for downstream tasks, such as POS-tagging, dependency-parsing, and so on.

## How to Use

```py
from transformers import AutoTokenizer,AutoModelForMaskedLM
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-tibetan")
model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-tibetan")
```