# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.

from sagemaker.jumpstart.model import JumpStartModel


model_id = "huggingface-zstc-recognai-zeroshot-selectra-medium"
endpoint_input = {'sequences': 'El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo', 'candidate_labels': ['cultura', 'sociedad', 'economia', 'salud', 'deportes']}

model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
print(f"Inference:\nInput: {endpoint_input}\nResponse: {response}\n")