> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nemo/curator/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server. # NeMo Curator Release Notes: 25.09 > Release notes and version history for NeMo Curator platform updates and new features This major release represents a fundamental architecture shift from [Dask](https://www.dask.org/) to [Ray](https://www.ray.io/), expanding NeMo Curator to support multimodal data curation with new [video](/curate-video) and [audio](/curate-audio) capabilities. This refactor enables unified backend processing, better heterogeneous computing support, and enhanced autoscaling for dynamic workloads. **Migrating from a previous version of NeMo Curator?** Refer to the [Migration Guide](/about/release-notes/migration-guide) for step-by-step instructions and the [Migration FAQ](/about/release-notes/migration-faq) for common questions. ## Installation Updates * **New Docker container**: Updated Docker infrastructure with CUDA 12.8.1 and Ubuntu 24.04 base; obtainable through the [NGC Catalog](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo-curator) (`nvcr.io/nvidia/nemo-curator:25.09`) * **Docker file to build own image**: Simplified [Dockerfile](https://github.com/NVIDIA-NeMo/Curator/blob/main/docker/Dockerfile) structure for custom container builds with FFmpeg support * **UV source installations**: Integrated UV package manager (v0.8.22) for faster dependency management * **PyPI improvements**: Enhanced PyPI installation with modular extras for targeted functionality: **Available Installation Extras** | Extra | Installation Command | Description | | ------------------ | ---------------------------- | --------------------------------------------------------- | | **All Modalities** | `nemo-curator[all]` | Complete installation with all modalities and GPU support | | **Text Curation** | `nemo-curator[text_cuda12]` | GPU-accelerated text processing with RAPIDS | | **Image Curation** | `nemo-curator[image_cuda12]` | Image processing with NVIDIA DALI | | **Audio Curation** | `nemo-curator[audio_cuda12]` | Speech recognition with NeMo ASR models | | **Video Curation** | `nemo-curator[video_cuda12]` | Video processing with GPU acceleration | | **Basic GPU** | `nemo-curator[cuda12]` | CUDA utilities without modality-specific dependencies | All GPU installations require the NVIDIA PyPI index: ```bash uv pip install https://pypi.nvidia.com nemo-curator[EXTRA] ``` ## New Modalities ### Video NeMo Curator now supports comprehensive [video data curation](/curate-video) with distributed processing capabilities: * **Video splitting**: [Fixed-stride](/curate-video/process-data/clipping) and [scene-change detection (TransNetV2)](/curate-video/process-data/clipping) for clip extraction * **Semantic deduplication**: [K-means clustering and pairwise similarity](/curate-video/process-data/dedup) for near-duplicate clip removal * **Content filtering**: [Motion-based filtering](/curate-video/process-data/filtering) and [aesthetic filtering](/curate-video/process-data/filtering) for quality improvement * **Embedding generation**: InternVideo2 and Cosmos-Embed1 models for clip-level embeddings * **Enhanced captioning**: [VL-based caption generation with optional LLM-based rewriting](/curate-video/process-data/captions-preview) (Qwen-VL and Qwen-LM supported) for detailed video descriptions * **Ray-based distributed architecture**: Scalable video processing with [autoscaling support](/about/concepts/video/architecture) ### Audio New [audio curation capabilities](/curate-audio) for speech data processing: * **ASR inference**: [Automatic speech recognition](/curate-audio/process-data/asr-inference) using NeMo Framework pretrained models * **Quality assessment**: [Word Error Rate (WER) and Character Error Rate (CER)](/curate-audio/process-data/quality-assessment) calculation * **Speech metrics**: [Duration analysis and speech rate metrics](/curate-audio/process-data/audio-analysis) (words/characters per second) * **Text integration**: Seamless integration with [text curation workflows](/curate-audio/process-data/text-integration) via `AudioToDocumentStage` * **Manifest support**: JSONL manifest format for audio file management ## Modality Refactors ### Text * **Ray backend migration**: Complete transition from Dask to Ray for distributed [text processing](/curate-text) * **Improved model-based classifier throughput**: Better overlapping of compute between tokenization and inference through [length-based sequence sorting](/curate-text/process-data/quality-assessment/distributed-classifier) for optimal GPU memory utilization * **Task-centric architecture**: New `Task`-based processing model for finer-grained control * **Pipeline redesign**: Updated `ProcessingStage` and `Pipeline` architecture with resource specification ### Image * **Pipeline-based architecture**: Transitioned from legacy `ImageTextPairDataset` to modern [stage-based processing](/curate-images) with `ImageReaderStage`, `ImageEmbeddingStage`, and filter stages * **DALI-based image loading**: New `ImageReaderStage` uses NVIDIA DALI for high-performance WebDataset tar shard processing with GPU/CPU fallback * **Modular processing stages**: Separate stages for [embedding generation](/curate-images/process-data/embeddings), [aesthetic filtering](/curate-images/process-data/filters/aesthetic), and [NSFW filtering](/curate-images/process-data/filters/nsfw) * **Task-based data flow**: Images processed as `ImageBatch` tasks containing `ImageObject` instances with metadata, embeddings, and classification scores Learn more about [image curation](/curate-images). ## Deduplication Improvements Enhanced deduplication capabilities across all modalities with improved performance and flexibility: * **Exact and Fuzzy deduplication**: Updated [rapidsmpf-based shuffle backend](/reference/infra/gpu-processing) for more efficient GPU-to-GPU data transfer and better spilling capabilities * **Semantic deduplication**: Support for deduplicating [text](/curate-text/process-data/deduplication/semdedup) and [video](/curate-video/process-data/dedup) datasets using unified embedding-based workflows * **New ranking strategies**: Added `RankingStrategy` which allows you to rank elements within cluster centers to decide which point to prioritize during duplicate removal, supporting [metadata-based ranking](/curate-text/process-data/deduplication/semdedup) to prioritize specific datasets or inputs ## Core Refactors The architecture refactor introduces a layered system with unified interfaces and multiple execution backends: ```mermaid graph LR subgraph "User Layer" P[Pipeline] S1[ProcessingStage X→Y] S2[ProcessingStage Y→Z] S3[ProcessingStage Z→W] R[Resources
CPU/GPU/NVDEC/NVENC] end subgraph "Orchestration Layer" BE[BaseExecutor Interface] end subgraph "Backend Layer" XE[XennaExecutor
Production Ready] RAP[RayActorPoolExecutor
Experimental] RDE[RayDataExecutor
Experimental] end subgraph "Adaptation Layer" XA[Xenna Adapter] RAPA[Ray Actor Adapter] RDA[Ray Data Adapter] end subgraph "Execution Layer" X[Cosmos-Xenna
Streaming/Batch] RAY1[Ray Actor Pool
Load Balancing] RAY2[Ray Data API
Dataset Processing] end P --> S1 P --> S2 P --> S3 S1 -.-> R S2 -.-> R S3 -.-> R P --> BE BE --> XE BE --> RAP BE --> RDE XE --> XA RAP --> RAPA RDE --> RDA XA --> X RAPA --> RAY1 RDA --> RAY2 style XE fill:#90EE90 style RAP fill:#FFE4B5 style RDE fill:#FFE4B5 style P fill:#E6F3FF style BE fill:#F0F8FF ``` ### Pipelines * **New Pipeline API**: Ray-based pipeline execution with `BaseExecutor` interface * **Multiple backends**: Support for [Xenna, Ray Actor Pool, and Ray Data execution backends](/reference/infra/execution-backends) * **Resource specification**: Configurable CPU and GPU memory requirements per stage * **Stage composition**: Improved stage validation and execution orchestration ### Stages * **ProcessingStage redesign**: Generic `ProcessingStage[X, Y]` base class with type safety * **Resource requirements**: Built-in resource specification for CPU and GPU memory * **Backend adapters**: Stage adaptation layer for different Ray orchestration systems * **Input/output validation**: Enhanced type checking and data validation ## Tutorials * **Text tutorials**: Updated all [text curation tutorials](https://github.com/NVIDIA-NeMo/Curator/tree/main/tutorials/text) to use new Ray-based API * **Image tutorials**: Migrated [image processing tutorials](https://github.com/NVIDIA-NeMo/Curator/tree/main/tutorials/image) to unified backend * **Audio tutorials**: New [audio curation tutorials](https://github.com/NVIDIA-NeMo/Curator/tree/main/tutorials/audio) * **Video tutorials**: New [video processing tutorials](https://github.com/NVIDIA-NeMo/Curator/tree/main/tutorials/video) For all tutorial content, refer to the [tutorials directory](https://github.com/NVIDIA-NeMo/Curator/tree/main/tutorials) in the NeMo Curator GitHub repository. ## Known Limitations > (Pending Refactor in Future Release) ### Generation * **Synthetic data generation**: Synthetic text generation features are being refactored for Ray compatibility * **Hard negative mining**: Retrieval-based data generation workflows under development ### PII * **PII processing**: Personal Identifiable Information removal tools are being updated for Ray backend * **Privacy workflows**: Enhanced privacy-preserving data curation capabilities in development ### Blending & Shuffling * **Data blending**: Multi-source dataset blending functionality being refactored * **Dataset shuffling**: Large-scale data shuffling operations under development ## Docs Refactor * **Local preview capability**: Improved documentation build system with local preview support * **Modality-specific guides**: Comprehensive documentation for each supported modality ([text](/curate-text), [image](/curate-images), [audio](/curate-audio), [video](/curate-video)) * **API reference**: Complete [API documentation](/api/reference/api-reference) with type annotations and examples --- ## What's Next The next release will focus on completing the refactor of Synthetic Data Generation, PII, and Blending & Shuffling features, along with additional performance optimizations and new modality support.