Cloudera Docs

What's New

Review the new features and improvements introduced in this release of Cloudera AI Workbench 2.0.55-h1000-b5, Cloudera AI Registry 1.13.0-h1000-b5, and Cloudera AI Inference service 1.10.0-h1000-b9.

Cloudera AI Inference service
  • You can now generate credentials to authenticate application requests or test model endpoints directly from the Model Endpoint Details page. For more information, see Authenticating with model endpoints.
  • Model endpoint creating and editing UI is now a guided, wizard-based flow that unifies model version selection, resource profiles, autoscaling, and review into a single experience. For more information, see Creating a Model Endpoint using UI.
  • When deploying Hugging Face models, you can now use an optional task selector in the UI to explicitly define operations such as text generation, embedding, or reranking. This selection is persisted in the deployment payload. For more information, see Creating a Model Endpoint using UI.
  • Cloudera AI Inference service now supports the deployment of the NVIDIA Magpie TTS Multilingual NIM runtime for high-quality text-to-speech (TTS) workloads. Using the new TEXT_TO_SPEECH task, you can generate multilingual synthetic speech in both offline (WAV) and streaming (LPCM) formats.
  • Cloudera AI Inference service now supports the NVIDIA Whisper Large v3 NIM for high-accuracy automatic speech recognition (ASR) workloads. Using the new riva_asr_whisper_large_v3_v140 runtime, you can deploy the latest v1.4.0 Whisper image to significantly improve transcription performance. Existing deployments using Whisper versions 1.3.0 and 1.3.1 remain fully supported and unchanged to ensure backward compatibility.
  • Cloudera AI Inference service now supports NVIDIA Parakeet 1.1B CTC EN-US NIM v1.4.0 for high-performance English speech-to-text workloads. Compared with larger models such as Whisper large-v3, Parakeet 1.1B is optimised for English-only use cases with a smaller model footprint, faster inference, and strong transcription accuracy for EN-US deployments. Users can deploy this model as a Riva ASR NIM through the Cloudera AI Inference service model catalog.
Cloudera AI Registry
  • Cloudera now offers a public Model Hub catalog, a curated external repository that allows you to browse and evaluate recommended NVIDIA NIMs and Hugging Face models before importing them. This standalone catalog accelerates model selection and simplifies collaboration by providing stakeholders outside of the Cloudera environment with direct visibility into supported AI assets.
Cloudera AI Workbench
  • Cloudera AI now provides an APIv2 endpoint that allows Administrators to upload and register ML Runtime add-ons. The API accepts the JSON ML Runtime add-on repository file, validates its contents, and then initiates asynchronous loading of the add-ons. Administrators can upload add-ons through the Swagger UI or by using command-line tools such as cURL. For more information, see Uploading ML Runtime add-on repository files.