This is T5-base model fine-tuned on SQuAD1.1 for QA using text-to-text approach
This model was trained on colab TPU with 35GB RAM for 4 epochs
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) 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'