add model card for t5-base-squad (#4409)
* add model card for t5-base-squad * Update model_cards/valhalla/t5-base-squad/README.md Co-authored-by: Julien Chaumond <chaumond@gmail.com>
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# T5 for question-answering
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This is T5-base model fine-tuned on SQuAD1.1 for QA using text-to-text approach
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## Model training
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This model was trained on colab TPU with 35GB RAM for 4 epochs
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## Results:
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| Metric | #Value |
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|-------------|---------|
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| Exact Match | 81.5610 |
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| F1 | 89.9601 |
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## Model in Action 🚀
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```
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from transformers import AutoModelWithLMHead, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("valhalla/t5-base-squad")
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model = AutoModelWithLMHead.from_pretrained("valhalla/t5-base-squad")
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def get_answer(question, context):
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input_text = "question: %s context: %s </s>" % (question, context)
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features = tokenizer.batch_encode_plus([input_text], return_tensors='pt')
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out = model.generate(input_ids=features['input_ids'],
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attention_mask=features['attention_mask'])
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return tokenizer.decode(out[0])
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context = "In Norse mythology, Valhalla is a majestic, enormous hall located in Asgard, ruled over by the god Odin."
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question = "What is Valhalla ?"
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get_answer(question, context)
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# output: 'a majestic, enormous hall located in Asgard, ruled over by the god Odin'
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```
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Play with this model [](https://colab.research.google.com/drive/1a5xpJiUjZybfU9Mi-aDkOp116PZ9-wni?usp=sharing)
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> Created by Suraj Patil [](https://github.com/patil-suraj/)
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[](https://twitter.com/psuraj28)
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