Zerpal
Collection
The largest open-source Udmurt monolingual corpora and pre-trained language models
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14 items
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Updated
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1
Zerpal-mBERT-tokenizer
How to use
You can use this model directly with a pipeline for masked language modeling:
from transformers import pipeline
unmasker = pipeline('fill-mask', model='udmurtNLP/zerpal-mbert', tokenizer='udmurtNLP/zerpal-mbert-tokenizer')
unmasker("Ӟечбур! Мынам нимы [MASK].")
Here is how to use this model to get the features of a given text in PyTorch:
from transformers import BertTokenizer, BertModel
tokenizer = BertTokenizer.from_pretrained('udmurtNLP/zerpal-mbert-tokenizer')
model = BertModel.from_pretrained("udmurtNLP/zerpal-mbert")
text = "Яратон, яратон, мар меда сыӵе тон?"
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no pipeline_tag.