Releasesby Glyphspark-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.
Also shipped Nov 7, 2025John Snow Labs in November 2025 →
Reduced compute pricing, more projects on Free plan, AI-powered onboarding release - Nov 07, 2025
Reduced compute pricing across Launch, Scale, and Agent plans. We've reduced compute pricing by up to 25% across our plans Launch plan Now $0.106 per CU hour (p...
What's new in Sigma
Data apps If/else control flow in action sequences (GA) If/else control flow is now generally available. Use if/else statements to create dynamic workflows within action sequences. If/else control flow adds flexibility to a sequence by allowing it to check one or more conditions and execute actions for the first condition that evaluates to true.
Workers automatic tracing, now in open beta
Enable automatic tracing on your Workers, giving you detailed metadata and timing information for every operation your Worker performs. Tracing helps you identify performance bottlenecks, resolve errors, and understand how your Worker interacts with other services on the Workers platform.
The little things, week ending November 7, 2025
A collection of updates to Replicate for the week ending November 7, 2025.
Expanded Language Detection: Now Supports 35 Languages for Pre-Recorded Audio
Language Detection for pre-recorded (batch) audio now supports 35 languages (previously 16), allowing you to automatically detect and transcribe a much broader array of languages with one request. Enable broader coverage by setting detect_language=true in your API call.
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 6.2.0
📢 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 6.2.3
📢 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.
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 6.3.1
📢 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 6.3.2
📢 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.