How do I save a pickled file to a GCP bucket from a jupyter environment?

I'm trying to save an arviz inference object as a pickle file to a gcp storage bucket using the following function:

def upload_to_bucket(model, blob_name, bucket_name):
    """ 
    model: trace object
    Upload data to a bucket"""
     
    # Explicitly use service account credentials by specifying the private key
    # file.
    storage_client = storage.Client.from_service_account_json(
        'key1.json')

    #print(buckets = list(storage_client.list_buckets())

    bucket = storage_client.get_bucket(bucket_name)
    blob = bucket.blob(blob_name)
    
    with open(f"gs://{config['GCS_bucket']}//{config['blob_name']}//", 'wb') as filehandler4:
        # Call load method to deserialze
        pickle.dump(model, filehandler4, protocol=4)
    
    #returns a public url
    return blob.public_url

upload_to_bucket(model=trace, blob_name='korea_hierarchy_seasonal_price.pkl', bucket_name='korea-forecasting-bucket')

However, I keep getting the following error:

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
/tmp/ipykernel_45766/484011007.py in <module>
----> 1 upload_to_bucket(model=trace, blob_name='korea_hierarchy_seasonal_price.pkl', bucket_name='korea-forecasting-bucket')

~/google_bucket.py in upload_to_bucket(model, blob_name, bucket_name)
     46     #     pickle.dump(model, filehandler4, protocol=4)
     47 
---> 48     with open(f"gs://{'GCS_bucket'}//{'blob_name'}//", 'wb') as filehandler4:
     49         # Call load method to deserialze
     50         pickle.dump(model, filehandler4, protocol=4)

FileNotFoundError: [Errno 2] No such file or directory: 'gs://GCS_bucket//blob_name//'

The answers to similar questions uses the gs moniker when saving to a gcp cloud storage so I'm not sure what I'm doing wrong.