
# 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)
```
{"language": ["en"], "library_name": "transformers", "datasets": ["squad_v2"], "pipeline_tag": "question-answering"}
transformers pytorch safetensors mobilebert question-answering en dataset:squad_v2 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #mobilebert #question-answering #en #dataset-squad_v2 #endpoints_compatible #has_space #region-us 


# 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

use question answering pipeline


# 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

use question answering pipeline
TAGS
#transformers #pytorch #safetensors #mobilebert #question-answering #en #dataset-squad_v2 #endpoints_compatible #has_space #region-us 
 # 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

use question answering pipeline
passage: TAGS
#transformers #pytorch #safetensors #mobilebert #question-answering #en #dataset-squad_v2 #endpoints_compatible #has_space #region-us 
# 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

use question answering pipeline