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NVIDIA AI Enterprise
NVIDIA AI Enterprise
  • NVIDIA NIM
    NVIDIA NIM
  • NIM Container GPUs
    NIM Container GPUs
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  • Displaying 26 results
    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
      Pretrained EG3D Models for FFHQ, AFHQ, and Shapenet Cars
      Model
      345M parameter GPT generative Megatron model
      Model
      Tacotron2 Speech Synthesis model trained on female English speech
      Model
      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
      AmberNet Lang ID model for Spoken Language Identification
      Model
      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
      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
      This resource is a Jupyter Notebook example that showcases NVIDIA Triton with Forest Inference Library (FIL) backend.
      Resource
      345M parameter BERT Megatron model with cased vocab
      Model
      Megatron 345m parameters model with biomedical vocabulary (50k size) cased, pre-trained on PubMed biomedical text corpus.
      Model
      End-to-end parallel speech synthesis model
      Model
      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
      RAD-TTS Aligner model trained on female English speech.
      Model
      345M parameter BERT Megatron model with uncased vocab
      Model
      Megatron 345m parameters model with biomedical vocabulary (50k size) uncased, pre-trained on PubMed biomedical text corpus.
      Model
      Megatron 345m parameters model with biomedical vocabulary (30k size) cased, pre-trained on PubMed biomedical text corpus.
      Model
      Training with WarpDrive
      Resource
      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
      Jupyter notebook for end-to-end training with WarpDrive
      Resource
      Megatron pretrained on uncased biomedical dataset PubMed with 345 million parameters.
      Model
      Megatron 345m parameters model with biomedical vocabulary (30k size) uncased, pre-trained on PubMed biomedical text corpus.
      Model