code: def log_model(
      path, name=None, metadata={}, description="trained model"
  ):
      "Log model file"
      if wandb.run is None:
          raise ValueError(
              "You must call wandb.init() before log_model()"
          )
      path = Path(path)
      if not path.is_file():
          raise f"path must be a valid file: {path}"
      name = ifnone(name, f"run-{wandb.run.id}-model")
      _format_metadata(metadata)
      artifact_model = wandb.Artifact(
          name=name,
          type="model",
          metadata=metadata,
          description=description,
      )
      with artifact_model.new_file(
          str(Path(name).with_suffix(".pth")), mode="wb"
      ) as fa:
          fa.write(path.read_bytes())
      wandb.run.log_artifact(artifact_model)
  
imports: from __future__ import annotations
  from ..basics import *
  from .progress import *
  from ..text.data import TensorText
  from ..tabular.all import TabularDataLoaders, Tabular
  from .hook import total_params
  from .tracker import SaveModelCallback
  import wandb
label_desc: Use image node_id 7 for calling a global function with example usage: log_model(path, name, metadata, description) without return types