Skip to main content
Page 1
>

Offline LLM Evaluation: Step-by-Step GenAI Application Assessment on Databricks

December 13, 2023 by Abe Omorogbe, Liang Zhang, Sunish Sheth, Corey Zumar, Maheswaran Venkatachalam, Emil Lysgaard and Mathias Christiansen in Engineering Blog
Background In an era where Retrieval-Augmented Generation (RAG) is revolutionizing the way we interact with AI-driven applications, ensuring the efficiency and effectiveness of...

Introducing MLflow 2.7 with new LLMOps capabilities

September 14, 2023 by Corey Zumar, Kasey Uhlenhuth and Ridhima Gupta in Machine Learning
As part of MLflow 2’s support for LLMOps, we are excited to introduce the latest updates to support prompt engineering in MLflow 2.7...

Using MLflow AI Gateway and Llama 2 to Build Generative AI Apps

August 23, 2023 by Kasey Uhlenhuth, Xiangrui Meng, Hagay Lupesko, Sean Owen, Corey Zumar, Liang Zhang, Ina Koleva, Vladimir Kolovski and Arpit Jasapara in Data Science and ML
To build customer support bots, internal knowledge graphs, or Q&A systems, customers often use Retrieval Augmented Generation (RAG) applications which leverage pre-trained models...

Announcing MLflow 2.4: LLMOps Tools for Robust Model Evaluation

June 7, 2023 by Corey Zumar, Hubert Zub, Kasey Uhlenhuth, Prithvi Kannan, Ridhima Gupta, Sunish Sheth, Harutaka Kawamura and Ann Zhang in Machine Learning
LLMs present a massive opportunity for organizations of all scales to quickly build powerful applications and deliver business value. Where data scientists used...

Introducing MLflow 2.3: Enhanced with Native LLMOps Support and New Features

April 17, 2023 by Ben Wilson, Harutaka Kawamura, Liang Zhang, Corey Zumar, Jin Zhang and Sunish Sheth in Platform Blog
With over 11 million monthly downloads, MLflow has established itself as the premier platform for end-to-end MLOps, empowering teams of all sizes to...

Announcing Ray support on Databricks and Apache Spark Clusters

February 27, 2023 by Weichen Xu, Ben Wilson, Jiajun Yao, Zhe Zhang, Eric Liang, Xiangrui Meng and Corey Zumar in Engineering Blog
Ray is a prominent compute framework for running scalable AI and Python workloads, offering a variety of distributed machine learning tools, large-scale hyperparameter...

Accelerate your model development with the new MLflow Experiments UI

February 16, 2023 by Ridhima Gupta, Hubert Zub, Prithvi Kannan, Apurva Koti, Sunish Sheth and Corey Zumar in Engineering Blog
MLflow is the premier platform for model development and experimentation. Thousands of data scientists use MLflow Experiment Tracking every day to find the...

Announcing Availability of MLflow 2.0

November 14, 2022 by Patrick Wendell, Craig Wiley, Xiangrui Meng, Corey Zumar and Ahmed Bilal in Platform Blog
MLflow , with over 13 million monthly downloads, has become the standard platform for end-to-end MLOps, enabling teams of all sizes to track...

Introducing MLflow Pipelines with MLflow 2.0

June 29, 2022 by Ahmed Bilal, Jin Zhang, Corey Zumar and Xiangrui Meng in Engineering Blog
Since we launched MLflow in 2018, MLflow has become the most popular MLOps framework, with over 11M monthly downloads! Today, teams of all...

Cross-version Testing in MLflow

March 11, 2022 by Harutaka Kawamura, Corey Zumar and Ben Wilson in Engineering Blog
MLflow is an open source platform that was developed to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry...
Next