<jupyter_start><jupyter_text>Model Monitoring Export function yaml<jupyter_code>from mlrun import code_to_function
from mlrun.runtimes import RemoteRuntime

fn: RemoteRuntime = code_to_function(
    name="model-monitoring-batch",
    kind="job",
    image="mlrun/mlrun",
    filename="model_monitoring_batch.py",
    handler="handler",
)

fn.export("model_monitoring_batch.yaml")<jupyter_output><empty_output><jupyter_text>Deploy Batch Processing<jupyter_code>from mlrun import import_function
from mlrun.platforms import mount_v3io
from mlrun.runtimes import KubejobRuntime


# Set project name
project = ""

fn: KubejobRuntime = import_function("hub://model_monitoring_batch")
fn.metadata.project = project
fn.apply(mount_v3io())
fn.run(name='model-monitoring-batch', schedule="0 */1 * * *", params={"project": project})<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11737089201877934, 'fraction_numerical': 0.004694835680751174, 'mean_word_length': 7.362745098039215, 'pattern_counts': {'":': 1, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '433581', 'license': 'Apache-2.0', 'n_tokens_mistral': 288, 'n_tokens_neox': 282, 'n_words': 49, 'path': 'model_monitoring_batch/model_monitoring_batch.ipynb', 'repo_name': 'grotesty/functions', 'size': '852'}