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dsfsi/zabantu-ven-120m
zabantu-ven-120m is a fill-mask model from dsfsi. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as cc.
This is a variant of Zabantu pre-trained on a monolingual dataset of Tshivenda(ven) sentences on a transformer network with 120 million traininable parameters.
Downloads · 30 days
13
3% of all-time downloads
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From the Hugging Face model README
This is a variant of Zabantu pre-trained on a monolingual dataset of Tshivenda(ven) sentences on a transformer network with 120 million traininable parameters.
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)