Create README.md (#5864)

model_cards/tuner007/t5_abs_qa/README.md

+# T5 for abstractive question-answering
+This is T5-base model fine-tuned for abstractive QA using text-to-text approach
+
+## Model training
+This model was trained on colab TPU with 35GB RAM for 2 epochs
+
+## Model in Action 🚀
+```
+from transformers import AutoModelWithLMHead, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("tuner007/t5_abs_qa")
+model = AutoModelWithLMHead.from_pretrained("tuner007/t5_abs_qa")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = model.to(device)
+
+def get_answer(question, context):
+input_text = "context: %s <question for context: %s </s>" % (context,question)
+features = tokenizer([input_text], return_tensors='pt')
+out = model.generate(input_ids=features['input_ids'].to(device), attention_mask=features['attention_mask'].to(device))
+return tokenizer.decode(out[0])
+```
+#### Example 1: Answer available
+```
+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: 'It is a hall of worship ruled by Odin.'
+```
+#### Example 2: Answer not available 
+```
+context = "In Norse mythology, Valhalla is a majestic, enormous hall located in Asgard, ruled over by the god Odin."
+question = "What is Asgard?"
+get_answer(question, context)
+# output: 'No answer available in context.'
+```
+
+
+> Created by Arpit Rajauria
+[![Twitter icon](https://cdn0.iconfinder.com/data/icons/shift-logotypes/32/Twitter-32.png)](https://twitter.com/arpit_rajauria)