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ZTamas/hubert-qa-milqa-impossible-long-answer
hubert-qa-milqa-impossible-long-answer is a question answering model from ZTamas. Use it when the input is a question plus a passage. It is set up for transformers.
This model is a fine-tuned version of mcsabai/huBert-fine-tuned-hungarian-squadv2 on the milqa dataset.
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From the Hugging Face model README
This model is a fine-tuned version of mcsabai/huBert-fine-tuned-hungarian-squadv2 on the milqa dataset.
How to use:
from transformers import pipeline
qa_pipeline = pipeline(
"question-answering",
model = "ZTamas/hubert-qa-milqa-impossible-long-answer",
tokenizer = "ZTamas/hubert-qa-milqa-impossible-long-answer",
device = 0, #GPU selection, -1 on CPU
handle_impossible_answer = True,
max_answer_len = 1000 #This can be modified, but to let the model's
#answer be as long as it wants so I
#decided to add a big number
)
predictions = qa_pipeline({
'context': context,
'question': question
})
print(predictions)