pytorch roberta text-classification en transformers boolean-qa
---
language: "en"
tags:
- boolean-qa
widget:
- text: "Is Berlin the smallest city of Germany?  <s> Berlin is the capital and largest city of Germany by both area and population. Its 3.8 million inhabitants make it the European Union's most populous city, according to the population within city limits "
---
# Labels Map
LABEL_0 => **"NO"** <br/>
LABEL_1 => **"YES"**


```python
from transformers import (
    AutoModelForSequenceClassification,
    AutoTokenizer,
)

model = AutoModelForSequenceClassification.from_pretrained("shahrukhx01/roberta-base-boolq")
model.to(device) 
#model.push_to_hub("roberta-base-boolq")

tokenizer = AutoTokenizer.from_pretrained("shahrukhx01/roberta-base-boolq")

def predict(question, passage):
  sequence = tokenizer.encode_plus(question, passage, return_tensors="pt")['input_ids'].to(device)
  
  logits = model(sequence)[0]
  probabilities = torch.softmax(logits, dim=1).detach().cpu().tolist()[0]
  proba_yes = round(probabilities[1], 2)
  proba_no = round(probabilities[0], 2)

  print(f"Question: {question}, Yes: {proba_yes}, No: {proba_no}")
  
passage = """Berlin is the capital and largest city of Germany by both area and population. Its 3.8 million inhabitants make it the European Union's most populous city, 
                        according to the population within city limits."""
 
question = "Is Berlin the smallest city of Germany?"
predict(s_question, passage)
```
