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---
license: cc
language:
- ve
metrics:
- perplexity
library_name: transformers
tags:
- tshivenda
- south africa
- low-resource
- bantu
- xlm-roberta
widget:
- text: "Rabulasi wa <mask> u khou bvelela nga u lima"
- text: "Vhana vhane vha kha ḓi bva u bebwa vha kha khombo ya u <mask> nga Listeriosis"
---
# Zabantu - Tshivenda
This is a variant of [Zabantu](https://huggingface.co/dsfsi/zabantu-bantu-250m) pre-trained on a monolingual dataset of Tshivenda(ven) sentences on a
transformer network with 120 million traininable parameters.
# Usage Example(s)
```python
from transformers import pipeline
# Initialize the pipeline for masked language model
unmasker = pipeline('fill-mask', model='dsfsi/zabantu-ven-120m')
sample_sentences = ["Rabulasi wa <mask> u khou bvelela nga u lima",
"Vhana vhane vha kha ḓi bva u bebwa vha kha khombo ya u <mask> nga Listeriosis"]
# Perform the fill-mask task
results = unmasker(sentence)
# Display the results
for result in results:
print(f"Predicted word: {result['token_str']} - Score: {result['score']}")
print(f"Full sentence: {result['sequence']}\n")
print("=" * 80)
```
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