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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 26 results
NVIDIA
NVIDIA
TitaNet-L
TitaNet model for Speaker Verification and Diarization tasks
Model
Tinker Tools
Tinker-HP
Tinker-HP is a CPUs and GPUs based, multi-precision, MPI massively parallel package dedicated to long polarizable molecular dynamics simulations and to polarizable QM/MM.
Container
NVIDIA
NVIDIA
Efficient Geometry-aware 3D Generative Adversarial Networks
Pretrained EG3D Models for FFHQ, AFHQ, and Shapenet Cars
Model
NVIDIA NeMo
NVIDIA NeMo
Megatron GPT2 345M
345M parameter GPT generative Megatron model
Model
NVIDIA
NVIDIA
TTS En Tacotron2
Tacotron2 Speech Synthesis model trained on female English speech
Model
NVIDIA
NVIDIA
BioMegatron345mUncased
Megatron pretrained on uncased biomedical dataset PubMed with 345 million parameters.
Model
Chunghwa Telecom Laboratories
SF Bilingual Speech in Chinese and English
A bilingual (Mandarin-English) Speech Dataset.
Resource
NVIDIA
NVIDIA
LangID Ambernet
AmberNet Lang ID model for Spoken Language Identification
Model
NVIDIA
NVIDIA
AzureML Quick Launch: TAO
Downloads pre-configured setup files to quick launch an NVIDIA TAO Jupyter Notebook on Azure Machine Learning with the appropriate resources (Compute Cluster and Environment). The set up is done using the NGC-AzureML Quick Launch Toolkit.
Resource
NVIDIA
NVIDIA
TTS Zh Fastpitch HifiGan SFSpeech
This model card includes two Mandarin Chinese models: 1) FastPitch Mel-spectrogram generator trained on SF Chinese/English Bilingual Speech dataset; 2) HiFiGAN vocoder trained on Mel-spectrograms predicted by the FastPitch.
Model
NVIDIA
NVIDIA
Triton FIL backend with XGBoost
This resource is a Jupyter Notebook example that showcases NVIDIA Triton with Forest Inference Library (FIL) backend.
Resource
NVIDIA NeMo
NVIDIA NeMo
Megatron-BERT 345M Cased
345M parameter BERT Megatron model with cased vocab
Model
NVIDIA NeMo
NVIDIA NeMo
BioMegatron345m-biovocab-50k-cased
Megatron 345m parameters model with biomedical vocabulary (50k size) cased, pre-trained on PubMed biomedical text corpus.
Model
—
TTS En VITS
End-to-end parallel speech synthesis model
Model
NVIDIA
NVIDIA
TTS DE Multi-Speaker FastPitch HiFiGAN
This collection includes two German models: FastPitch trained on the HUI-Audio-Corpus-German clean dataset where the 5-largest amount of speakers are selected and balanced; HiFiGAN is trained on mel-spectrograms predicted by the Multi-speaker FastPitch.
Model
NVIDIA
NVIDIA
TTS En RAD-TTS Aligner
RAD-TTS Aligner model trained on female English speech.
Model
NVIDIA NeMo
NVIDIA NeMo
Megatron-BERT 345M Uncased
345M parameter BERT Megatron model with uncased vocab
Model
NVIDIA NeMo
NVIDIA NeMo
BioMegatron345m-biovocab-50k-uncased
Megatron 345m parameters model with biomedical vocabulary (50k size) uncased, pre-trained on PubMed biomedical text corpus.
Model
NVIDIA NeMo
NVIDIA NeMo
BioMegatron345m-biovocab-30k-cased
Megatron 345m parameters model with biomedical vocabulary (30k size) cased, pre-trained on PubMed biomedical text corpus.
Model
NVIDIA NeMo
NVIDIA NeMo
FinMegatron345m-gpt2-bpe
FSI : Financial Megatron GPT2 345m parameters model with BPE tokenizer, gpt vocabulary and merge file, pre-trained on subsets of CC-100 text corpus.
Model
Salesforce
Salesforce
Training with WarpDrive
Training with WarpDrive
Resource
NVIDIA NeMo
NVIDIA NeMo
BioMegatron345mUncased
Megatron pretrained on uncased biomedical dataset PubMed with 345 million parameters.
Model
Salesforce
Salesforce
End-to-end Training with WarpDrive
Jupyter notebook for end-to-end training with WarpDrive
Resource
NVIDIA NeMo
NVIDIA NeMo
BioMegatron345m-biovocab-30k-uncased
Megatron 345m parameters model with biomedical vocabulary (30k size) uncased, pre-trained on PubMed biomedical text corpus.
Model