class_docstr: An MLflow Model that can support multiple model flavors. Provides APIs for implementing
  new Model flavors.
class_docstr_tok: ["An","MLflow","Model","that","can","support","multiple","model","flavors",".","Provides","APIs","for","implementing","new","Model","flavors","."]
docstr: Add an entry for how to serve the model in a given format.
docstr_tok: ["Add","an","entry","for","how","to","serve","the","model","in","a","given","format","."]
code: def add_flavor(self, name, **params):
      """Add an entry for how to serve the model in a given format."""
      self.flavors[name] = params
      return self
  
imports: import json
  import logging
  import os
  import uuid
  import warnings
  from datetime import datetime
  from typing import Any, Callable, Dict, Optional, Union
  import yaml
  import mlflow
  from mlflow.artifacts import download_artifacts
  from mlflow.exceptions import MlflowException
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking._tracking_service.utils import _resolve_tracking_uri
  from mlflow.utils.annotations import experimental
  from mlflow.utils.databricks_utils import get_databricks_runtime
  from mlflow.utils.file_utils import TempDir
  from mlflow.utils.uri import get_uri_scheme
label_desc: Use image node_id 8 for calling the Model obj's underlying member method code with example usage: obj.add_flavor(name) and returns: self