I’m trying to download artifacts and a model that has been saved using MLflow on GitLab model registry. That's the working part of my code, where I set up the client, create model and version and upload artifact previously saved on a local folder: # Running client import os from mlflow import MlflowClient os.environ["MLFLOW_TRACKING_URI"] = "..." os.environ["MLFLOW_TRACKING_TOKEN"] = "..." client = MlflowClient() # Model and version creation model_name = 'test_model_n' description = 'test model' model = client.create_registered_model(model_name, description=description) model_version = '1.0.1' tags = { "gitlab.version": model_version } model_version = client.create_model_version(model_name, model_version, tags=tags) # Logging artifacts run_id = model_version.run_id client.log_artifact(run_id, 'mlartifacts/875771393960734527', artifact_path="") Now, in order to fetch the model i tried multiple approaches: Method 1 model_uri = f"models:/{model_name}/{model_version}" model = mlflow.pyfunc.load_model(model_uri) Download bar reach 100%, but a warning and an error pops out: WARNING:urllib3.connectionpool:Connection pool is full, discarding connection: "gitlab server" Connection pool size: 10 Could not find a registered artifact repository for: c:. Currently registered schemes are: ['', 'file', 's3', 'r2', 'gs', 'wasbs', 'ftp', 'sftp', 'dbfs', 'hdfs', 'viewfs', 'runs', 'models', 'http', 'https', 'mlflow-artifacts', 'abfss'] Method 2 artifacts_path, = mlflow.artifacts.download_artifacts( run_id=run_id, artifact_path="", dst_path="./downloaded_model" Error: ValueError: not enough values to unpack (expected 2, got 1) Method 3 # Se conosci il run_id specifico mv = client.get_model_version(model_name, model_version) run_id = mv.run_id # Costruisci l'URI usando il run_id run_uri = f"runs:/{run_id}/[path_to_the_model]" model_from_run = mlflow.pyfunc.load_model(run_uri) Error: ValueError: not enough values to unpack (expected 2, got 1) Any help would be very appreciated, feel free to ask for more info if you think it would help. Continue reading...