Hi,

I have a PyTorch model which I have pushed into the **dbfs** now I want to serve the model using MLflow. I saw that the model needs to be in **python_function model**.

To do that I did the following methods

1. load the model from dbfs using torch load option

2. Then save the model in python_function model using the pyfunc.save_model function

3. After this when I register the model I get a decode error

I'm not training any model in the Databricks.

```
import mlflow
import mlflow.pyfunc
from torch import load as torch_load
py_model = torch_load( "/dbfs/FileStore/ml/ner_model" , map_location = torch_device(ner_gpu_device))
mlflow.pytorch.save_model(py_model,path="/dbfs/FileStore/pyfunc/ner_model")
model = mlflow.pyfunc.load_model("/dbfs/FileStore/pyfunc/ner_model")
mlflow.register_model(model,"ner_model")
# loading the python_function model to register
model = mlflow.pyfunc.load_model("/dbfs/FileStore/pyfunc/ner_model")
model_version = mlflow.register_model(model,"ner_model")
```

**this is the error which I get while running the register model line**