Edit model card

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)
Downloads last month
11
Safetensors
Model size
24.6M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train aware-ai/mobilebert-squadv2