# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("aware-ai/mobilebert-squadv2")
model = AutoModelForQuestionAnswering.from_pretrained("aware-ai/mobilebert-squadv2", device_map="auto")Quick Links
Mobile-Bert fine-tuned on Squad V2 dataset
This is based on mobile bert architecture suitable for handy devices or device with low resources.
usage
using transformers library first load model and Tokenizer
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
model_name = "aware-ai/mobilebert-squadv2"
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
use question answering pipeline
qa_engine = pipeline('question-answering', model=model, tokenizer=tokenizer)
QA_input = {
'question': 'your question?',
'context': '. your context ................ '
}
res = qa_engine (QA_input)
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# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="aware-ai/mobilebert-squadv2")