readme: # T5 for question-answering
  This is T5-base model fine-tuned on SQuAD1.1 for QA using text-to-text approach
  
  ## Model training
  This model was trained on colab TPU with 35GB RAM for 4 epochs
  
  ## Results:
  | Metric      | #Value  |
  |-------------|---------|
  | Exact Match | 81.5610 |
  | F1          | 89.9601 |
  
  ## Model in Action 🚀
  ```
  from transformers import AutoModelWithLMHead, AutoTokenizer
  
  tokenizer = AutoTokenizer.from_pretrained("valhalla/t5-base-squad")
  model = AutoModelWithLMHead.from_pretrained("valhalla/t5-base-squad")
  
  def get_answer(question, context):
    input_text = "question: %s  context: %s </s>" % (question, context)
    features = tokenizer([input_text], return_tensors='pt')
  
    out = model.generate(input_ids=features['input_ids'], 
                 attention_mask=features['attention_mask'])
    
    return tokenizer.decode(out[0])
  
  context = "In Norse mythology, Valhalla is a majestic, enormous hall located in Asgard, ruled over by the god Odin."
  question = "What is Valhalla ?"
  
  get_answer(question, context)
  # output: 'a majestic, enormous hall located in Asgard, ruled over by the god Odin'
  ```
  Play with this model [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1a5xpJiUjZybfU9Mi-aDkOp116PZ9-wni?usp=sharing)
  
  > Created by Suraj Patil [![Github icon](https://cdn0.iconfinder.com/data/icons/octicons/1024/mark-github-32.png)](https://github.com/patil-suraj/)
  [![Twitter icon](https://cdn0.iconfinder.com/data/icons/shift-logotypes/32/Twitter-32.png)](https://twitter.com/psuraj28)
  