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README.md

@@ -23,7 +23,7 @@ onnx_model = InferenceSession(onnx_path, providers=['CPUExecutionProvider'])
 
 context = 'ONNX is an open format to represent models. The benefits of using ONNX include interoperability of frameworks and hardware optimization.'
 question = 'What are advantages of ONNX?'
-tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
+tokenizer = AutoTokenizer.from_pretrained('UKP-SQuARE/bert-base-uncased-pf-squad_v2-onnx')
 
 inputs = tokenizer(question, context, padding=True, truncation=True, return_tensors='np')
 inputs_int64 = {key: np.array(inputs[key], dtype=np.int64) for key in inputs}