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from openvino.runtime import Core
import numpy as np
# Initialize the OpenVINO runtime Core
ie = Core()
# Load and compile the model for the CPU device
compiled_model = ie.compile_model(model='../ovc_output/converted_model.xml', device_name="CPU")
# Prepare input: a non tokenized example just for examples sake
input_ids = np.random.randint(0, 50256, (1, 10))
# Create a dictionary for the inputs expected by the model
inputs = {"input_ids": input_ids}
# Create an infer request and start synchronous inference
result = compiled_model.create_infer_request().infer(inputs=inputs)
# Access output tensor data directly from the result using the appropriate output key
output = result['outputs']
print("Inference results:", output)
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