Releasesby Glyphspark-nlp 6.2.3
📢 Spark NLP 6.2.3: Further Improvements for NerDL Spark NLP 6.2.3 introduces targeted improvements to training performance and stability of NerDLApproach and bug fixes for CamemBertForTokenClassification. NerDLApproach now uses new internal data-loading behavior, and improving training speed and preventing out-of-memory errors.
Also shipped Dec 3, 2025John Snow Labs in December 2025 →
Introducing Seven New Email Templates for Supabase Auth
Supabase Auth introduced seven new email templates to notify users of security-sensitive account actions.
The new Supabase power for Kiro
The Kiro IDE now provides deep integration with Supabase, assisting developers with database migrations, edge functions, and security policies.
EU Endpoint Now Generally Available
The Deepgram EU endpoint ( api.eu.deepgram.com ) is now generally available for customers requiring data processing within the European Union.
How we built user behavior analysis with multi-modal LLMs (in 5 not-so-easy steps)
PostHog released Session Summaries in beta, a tool that uses multi-modal LLMs to analyze user session recordings and highlight issues automatically.
eAPM General Availability and eBPF Network Metrics Public Preview
Background Our customers are faced with these challenges: The first challenge is the traditional observability gap. Traditional APM tools lack kernel-level network and system metrics. This means that during an incident, it is difficult to pinpoint the root cause between application code issues and network-related issues.
NeMo NVIDIA Neural Modules 2.6.0
Highlights Speech Add Timestamps to streaming ASR PR Add Streaming decoding policies (Wait-K and AlignAtt) for Canary model PR Add NeMo Voice Agent PR Hybrid RNNT-CTC Prompted Parakeet Model support PR [New] MT-Parakeet Streaming Models release Removed the Automodel module. Automodel is available in the repo https://github.com/NVIDIA-NeMo/Automodel .
More from spark-nlpEvery spark-nlp release →
spark-nlp 6.2.2
📢 Spark NLP 6.2.2: Bugfix Release Spark NLP 6.2.2 brings bug fixes to WordEmbeddings and NerDLApproach logging. 🐛 Bug Fixes - WordEmbeddings: Fixed a bug where WordEmbeddings would duplicate input tokens in the output - NerDLApproach: Fixed a bug during logging, that would show inaccurate training/validation counts.
spark-nlp 6.2.1
📢 Spark NLP 6.2.1: Enhanced hierarchical document processing and training optimizations Spark NLP 6.2.1 brings significant improvements to document ingestion with expanded hierarchical support, XML processing enhancements, and optimizations for NerDL training.
spark-nlp 6.3.1
📢 Spark NLP 6.3.1: LLM Backend Upgrade and Document Processing Improvements Spark NLP 6.3.1 focuses on strengthening distributed local LLM inference by upgrading the jsl-llamacpp backend to a newer llama.cpp release, while also delivering important improvements in document structure handling and metadata consistency.
spark-nlp 6.2.0
📢 Spark NLP 6.2.0: A new stage for unstructured document ingestion and processing at scale Spark NLP 6.2.0 introduces key upgrades across entity extraction, document normalization, HTML reading, and GGUF-based models.
spark-nlp 6.1.5
📢 Spark NLP 6.1.5: Smarter Readers and More Resilient Pipelines Spark NLP 6.1.5 focuses on improving data ingestion reliability and pipeline flexibility. This release enhances reader components with better fault tolerance, broader input support, and introduces a new ReaderAssembler annotator for streamlined integration.
spark-nlp 6.3.2
📢 Spark NLP 6.3.2: Scala 2.13 Support, Layout-Aware Images, and Enhanced LightPipeline Tracking Spark NLP 6.3.2 is a foundational release that introduces official support for Scala 2.13, alongside important improvements in document layout understanding and lightweight inference workflows.
spark-nlp 6.3.3
📢 Spark NLP 6.3.3: ModernBERT Embeddings, Vector DB Integration, and Layout-Aware Document Processing Spark NLP 6.3.3 is a feature-packed release aimed at practitioners building modern NLP and multimodal document pipelines.
spark-nlp 6.4.0
📢 Spark NLP 6.4.0: LLM-Powered Entity Extraction, Expanded Document Readers, and Pipeline Robustness Spark NLP 6.4.0 is a feature-rich release focused on bringing LLM-powered extraction into standard NLP pipelines, dramatically expanding the document reader ecosystem, and hardening production ingestion workflows.