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Here is some model I created:class SomeModel(mlflow.pyfunc.PythonModel):
def predict(self, context, input):
# do fancy ML stuff
# log results
pandas_df = pd.DataFrame(...insert predictions here...)
spark_df = spark...
We are using Databricks over AWS infra, registering models on mlflow. We write our in-project imports as from src.(module location) import (objects).Following examples online, I expected that when I use mlflow.pyfunc.log_model(...code_path=['PROJECT_...
Hi @Idan Reshef Thank you for posting your question in our community! We are happy to assist you.To help us provide you with the most accurate information, could you please take a moment to review the responses and select the one that best answers y...
I am using Databricks AutoML ( Python SDK) to forecast bed occupancy. (Actually, Databricks used MLflow experiments for AutoML run). After training with different iterations, I registered the best model in the Databricks Model registry. Now I am tryi...
Hi, It can be a bug if the python version is 3.9.5 and still the error is on compatibility. Could you please raise a support case to look into it further?
When I log a pyfunc mlflow model, it generates a page that has this helpful code for using the model in production. Make Predictions
Predict on a Spark DataFrame:
import mlflow
from pyspark.sql.functions import struct, col
logged_model = 'runs:/1d......
Hi @Shawn Feng Does @Atanu Sarkar response answer your question? If yes, would you be happy to mark it as best so that other members can find the solution more quickly?We'd love to hear from you.Thanks!
Hello, I am training a logistic regression on text with the help of an tf-idf vectorizer.This is done with MLflow and sklearn in databricks.The model itself is trained successfully in databricks and it is possible to accomplish predictions within the...
I'm trying to deploy a ml model into production using mlflow. while in that process, I have registered the model to mlflow models. After that it created the cluster but then it was in pending state forever. when I checked the model events, I see a pr...
I'm trying to deploy a ml model into production using mlflow. while in that process, I have registered the model to mlflow models. After that it created the cluster but then it was in pending state forever. when I checked the model events, I see a p...
Hey @ravi g Does @Kaniz Fatma's answer help? If it does, would you be happy to mark it as best? If it doesn't, please tell us so we can help you.Thanks!
Is it possible to create mlflow model as a docker image with REST api endpoint and use it for inferencing within databricks or hosting the image in azure container instances?
@Vijeth Moudgalya , Hey there, we are definitely interested in making model serving easier and simpler on Databricks. There are some useful product features coming down the line - contact me at bilal dot aslam at databricks dot com if you are intere...
ML flow model serving in Databricks docs details the options to enable and disable from the UIhttps://docs.databricks.com/applications/mlflow/model-serving.html
Please find below the REST APIs to enable and disable Model-ServingBelow are the examples in PythonYou need to use the token to interact with Rest APItoken = "dxxxxxx"instance = "https://<workspacexxx>.cloud.databricks.com"headers = {'Authorization':...
