| 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) | |