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SearchSearch thousands of GPU-optimized Containers, pretrained Models, SDKs, and Helm charts—ready to accelerate AI, digital twins, and HPC from cloud to edge.
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Displaying 119 results
NVIDIA
NVIDIA
Triton Inference Server
Triton Inference Server is an open source software that lets teams deploy trained AI models from any framework, from local or cloud storage and on any GPU- or CPU-based infrastructure in the cloud, data center, or embedded devices.
Container
NVIDIA
NVIDIA
Riva Speech Skills
Riva Speech Skills is a scalable Conversational AI service platform.
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
Whisper Large v3 - Speech to Text
Robust Speech Recognition via Large-Scale Weak Supervision.
Container
NVIDIA
NVIDIA
Riva Skills Quick Start
Scripts and utilities for getting started with Riva Speech Skills
Resource
NVIDIA
NVIDIA
Kaldi
Kaldi is an open-source software framework for speech processing.
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
Parakeet TDT 0.6B v2 Speech to Text
Accurate and optimized English transcriptions with punctuation and word timestamps
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
Parakeet CTC 0.6B Vietnames English ASR
Accurate and optimized Vietnamese English transcriptions with punctuation and word timestamps
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
Parakeet CTC 0.6B Mandarin English ASR
Accurate and optimized Mandarin English transcriptions with punctuation and word timestamps
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
Nemotron 3 ASR
Nemotron ASR Streaming
Container
NVIDIA Developer Program
NVIDIA
NVIDIA
Parakeet CTC 0.6B Taiwanese Mandarin-English ASR
Parakeet-0.6B hybrid-RNNT training with CTC head for zh-tw streaming ASR. Supports Taiwanese Mandarin (zh-tw) and light code-switching capability for Taiwanese Mandarin-English.
Container
NVIDIA
NVIDIA
Diarization MSDD Telephonic
Multi-scale Diarization Decoder (MSDD) model for speaker diarization of telephone conversations
Model
NVIDIA
NVIDIA
Domain Specific NeMo ASR Application
The Domain Specific - NeMo Automatic Speech Recognition (ASR) Application facilitates training, evaluation and performance comparison of ASR models. This NeMo application enables you to train or fine-tune pre-trained ASR models with your own data.
Container
NVIDIA
NVIDIA
Voice Demo for Jetson/L4T
ASR + BERT QA interactive chatbot demo for Jetson
Container
NVIDIA
NVIDIA
STT En Citrinet 1024 Gamma 0.25
Citrinet 1024 with kernel scaling factor (gamma) of 25% trained on ASR Set dataset
Model
NVIDIA
NVIDIA
Speech to Text Notebook
End to End workflow for speech to text training with TAO Toolkit and deployment using Riva.
Resource
NVIDIA
NVIDIA
STT Zh Citrinet 1024 Gamma 0.25
Citrinet-1024 model with kernel scaling factor (gamma) of 25%, which has been trained on the open-source Aishell-2 Mandarin Chinese corpus.
Model
NVIDIA
NVIDIA
Speech to Text Citrinet Notebook
End to End workflow for speech to text citrinet training with TAO Toolkit and deployment using Riva.
Resource
NVIDIA
NVIDIA
Audio Codec 16kHz Small
This model card contains a Small Audio Codec model trained on the Libri-Light audiobook recordings dataset, comprising approximately 60,000 hours of English language speech with a 16kHz sampling rate.
Model
NVIDIA
NVIDIA
STT En Conformer-CTC XLarge
Conformer-CTC-XLarge model for English Automatic Speech Recognition, Trained on NeMo ASRSET
Model
NVIDIA
NVIDIA
STT DE Citrinet 1024
German Citrinet 1024 model.
Model
NVIDIA
NVIDIA
STT En Conformer-CTC Large LibriSpeech
Conformer-CTC-Large model for English Automatic Speech Recognition, Trained with NeMo on LibriSpeech dataset
Model
NVIDIA
NVIDIA
LangID Ambernet
AmberNet Lang ID model for Spoken Language Identification
Model
NVIDIA
NVIDIA
STT Ru Conformer-CTC Large
Conformer-CTC-Large model for Russian Automatic Speech Recognition, trained on Mozilla Common Voice 10.0 (Russian), Golos (Russian), Russian LibriSpeech (RuLS) and SOVA (RuAudiobooksDevices, RuDevices) datasets.
Model
NVIDIA
NVIDIA
STT Multilingual FastConformer Hybrid Transducer-CTC Large P&C
The large version (114M) of the Multilingual speech recognition model with a FastConformer encoder and a Hybrid decoder (joint RNNT-CTC loss). The model has a vocab size of 2560 and emits text with punctuation and capitalization.
Model

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