ReleaseMicrosoftMicrosoftpublished Nov 20, 2025seen Jun 26

microsoft/SynapseML v1.1.0

microsoft/SynapseML

Open original ↗

Captured source

source ↗
published Nov 20, 2025seen Jun 26captured 2whttp 200method plain

SynapseML v1.1.0

Repository: microsoft/SynapseML

Tag: v1.1.0

Published: 2025-11-20T03:51:26Z

Prerelease: no

Release notes:

##### We are excited to announce the release of SynapseML v1.1 marking a host of powerful new features introduced since the initial v1.0 release. SynapseML is an open-source library that aims to streamline the development of massively scalable machine learning pipelines. It unifies several existing ML Frameworks and new Microsoft algorithms in a single, scalable API that is usable across Python, R, Scala, and Java. SynapseML is usable from any Apache Spark platform with first class enterprise support on Microsoft Fabric.

Highlights

| | | | |:--:|:--:|:--:| |Microsoft Fabric | AI Functions | OneLake | | Build and operationalize distributed ML with SynapseML in Fabric | Apply Pandas and Spark LLM transformations with one line of code | Automatically derive AI insights for unstructured data in OneLake | | Build Your First Model | Explore AI Functions | Learn More |

| | | |:--:|:--:| |Hugging Face | Azure AI Foundry | | Use open source models hosted on Hugging Face | Run Azure AI Foundry models in your notebook | | Try an Example | View Notebook |

More Hightlights

Spark 3.5 Support – In this version we transitioned to Spark 3.5 as our main Spark platform.

OpenAI Ecosystem – Comprehensive improvements including global parameter defaults, GPT-4 enablement, custom endpoints/headers, GPU-accelerated embeddings with KNN, and fine-grained control over model parameters (top_p, seed, responseFormat, temperature).

ML Innovation – HuggingFaceCausalLM transformer for distributed language model evaluation, custom embedder support, and synthetic difference-in-differences causal inference module.

Platform features – Spark Native OneLake support; MSI for Azure Storage; OpenAITranslate transformer.

AI Functions in Data Wrangler on Fabric – AI Functions built into Data Wrangler in Fabric allow you to apply LLM-powered operations to your dataframe without writing a single line of code.

New Features

Documentation 📚

AI Functions ⚡

Azure OpenAI 🌸

  • Enhanced Model Parameters – Added top_p, seed, responseFormat, temperature, and subscription key support (#2410, #2329,...

Excerpt shown — open the source for the full document.