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from transformers import AutoTokenizer, TFAutoModelForQuestionAnswering
import tensorflow as tf
checkpoint = "distilbert-base-cased-distilled-squad"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = TFAutoModelForQuestionAnswering.from_pretrained(checkpoint)
def question_answering_tf(question, context):
inputs = tokenizer(question, context, return_tensors="tf")
#print(inputs["input_ids"])
#print(tokenizer.decode(inputs["input_ids"][0]))
outputs = model(inputs)
#print(outputs.start_logits)
#print(outputs.end_logits)
start_index = int(tf.math.argmax(outputs.start_logits, axis=-1)[0])
end_index = int(tf.math.argmax(outputs.end_logits, axis=-1)[0])
print(start_index, end_index)
return tokenizer.decode(inputs["input_ids"][0][start_index: end_index+1]) |