Xlm Roberta Large Squad2 Qa Milqa Impossible

🚀 ZTamas/xlm-roberta-large-squad2-qa-milqa-impossible

This model is a fine - tuned version of deepset/xlm - roberta - large - squad2 on the milqa dataset, designed for question - answering tasks.

🚀 Quick Start

This model is a fine - tuned version of deepset/xlm - roberta - large - squad2 on the milqa dataset.

📦 Installation

Packages to install for large roberta model:

sentencepiece==0.1.97
protobuf==3.20.0

💻 Usage Examples

Basic Usage

from transformers import pipeline
qa_pipeline = pipeline(
  "question-answering",
  model = "ZTamas/xlm-roberta-large-squad2-qa-milqa-impossible",
  tokenizer = "ZTamas/xlm-roberta-large-squad2-qa-milqa-impossible",
  device = 0,                      #GPU selection, -1 on CPU
  handle_impossible_answer = True,
  max_answer_len = 50              #This can be modified
  )

predictions = qa_pipeline({
    'context': context,            
    'question': question           
})

print(predictions)

Advanced Usage

# You can adjust parameters according to your specific needs, such as changing the device, handling impossible answers, and setting the maximum answer length.
from transformers import pipeline
qa_pipeline = pipeline(
  "question-answering",
  model = "ZTamas/xlm-roberta-large-squad2-qa-milqa-impossible",
  tokenizer = "ZTamas/xlm-roberta-large-squad2-qa-milqa-impossible",
  device = 0,                      #GPU selection, -1 on CPU
  handle_impossible_answer = True,
  max_answer_len = 50              #This can be modified
  )

predictions = qa_pipeline({
    'context': context,            
    'question': question           
})

print(predictions)