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  • Displaying 56 results
    NVIDIA
    NVIDIA
    Kaldi
    Kaldi is an open-source software framework for speech processing.
    Container
    NVIDIA
    NVIDIA
    Text Classification with BERT and NeMo
    Text Classification with BERT and NeMo. This NeMo application trains text classification models using single-GPU or multi-GPU. We log performance metrics and visualize them with TensorBoard. We show how to do inference with NeMo, and we visualize BERT embeddings before and after fine-tuning.
    Container
    DeepPavlov
    DeepPavlov
    DeepPavlov is an open-source conversational AI library built on TensorFlow and Keras. DeepPavlov is designed for development of production ready chatbots and complex conversational systems, research in the area of NLP and, particularly, of dialog systems.
    Container
    NVIDIA
    NVIDIA
    Fine-Tune and Optimize BERT
    Jupyter Notebooks for BERT Pre-training, Fine-Tuning and Inference profiling and optimization via TensorFlow, AMP, XLA, DLProf, TF-TRT and Triton.
    Container
    NVIDIA NeMo
    NVIDIA NeMo
    Megatron GPT2 345M
    345M parameter GPT generative Megatron model
    Model
    NVIDIA
    NVIDIA
    BertBaseUncasedForNemo
    BERT Base Model trained on uncased Wikipedia and BookCorpus dataset on a sequence length of 512.
    Model
    —
    BioMegatron345mCased
    Megatron pretrained on cased biomedical dataset PubMed with 345 million parameters.
    Model
    NVIDIA
    NVIDIA
    BertLargeUncasedForNemo
    BERT Large Model trained with NeMo on uncased Wikipedia and Bookcorpus on a sequence length 512.
    Model
    NVIDIA
    NVIDIA
    BioMegatron345mUncasedSQuADv1
    BioMegatron 345M uncased model for Question Answering finetuned with NeMo on SQuAD v1.1 dataset.
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    BERT PyTorch checkpoint (Dist-4L-288D, SQuAD1, seqLen384, AMP)
    BERT Distilled 4L-288D PyTorch checkpoint distilled on SQuAD v1.1 dataset using AMP
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    BERT PyTorch checkpoint (Large, SST-2, seqLen128, AMP)
    BERT Large PyTorch checkpoint finetuned on GLUE/SST-2 dataset using AMP
    Model
    NVIDIA
    NVIDIA
    BertBaseCasedForNeMo
    BERT Base Model trained with NeMo on cased Wikipedia and BookCorpus on a sequence length of 512.
    Model
    NVIDIA
    NVIDIA
    BertBaseUncasedSQuADv1
    BERT Base Uncased model for Question Answering finetuned with NeMo on SQuAD v1.1 dataset.
    Model
    Nvidia
    Nvidia
    BioBERTBaseCasedForNeMo
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    Bert Large checkpoint (TensorFlow2, AMP, Squad1.1, seqLen384)
    Bert Large TensorFlow2 checkpoint finetuned on Squad1.1 using seqLen=384
      Model
      NVIDIA
      NVIDIA
      TRADE - MultiWOZ 2.0 - Dialogue State Tracker
      Checkpoint of TRADE model for dialogue state tracking trained on MultiWOZ 2.0 dataset using NeMo.
      Model
      NVIDIA
      NVIDIA
      TRADE - MultiWOZ 2.1 - Dialogue State Tracker
      Checkpoint of TRADE model for dialogue state tracking trained on MultiWOZ 2.1 dataset using NeMo.
      Model
      NVIDIA Deep Learning Examples
      NVIDIA Deep Learning Examples
      BERT PaddlePaddle checkpoint (Large, Pretraining, AMP, LAMB)
      BERT Large PaddlePaddle checkpoint pretrained with LAMB optimizer using AMP
        Model
        NVIDIA Deep Learning Examples
        NVIDIA Deep Learning Examples
        BERT PyTorch checkpoint (Dist-6L-768D, SQuAD1, AMP)
        BERT Distilled 6L-768D PyTorch checkpoint distilled on SQuAD v1.1 dataset using AMP
        Model
        NVIDIA Deep Learning Examples
        NVIDIA Deep Learning Examples
        BERT PyTorch checkpoint (Base, Pretraining, AMP, LAMB)
        BERT Base PyTorch checkpoint pretrained with LAMB optimizer using AMP
          Model
          NVIDIA Deep Learning Examples
          NVIDIA Deep Learning Examples
          BERT PyTorch checkpoint (Dist-6L-768D, Pretraining, AMP)
          BERT Distilled 6L-768D PyTorch Phase2 checkpoint pretrained using 67K steps on seqLen128 and 6k steps on seqLen512
          Model
          NVIDIA Deep Learning Examples
          NVIDIA Deep Learning Examples
          BERT PyTorch checkpoint (Dist-4L-288D, Pretraining, AMP)
          BERT Distilled 4L-288D PyTorch checkpoint distilled on pretraining dataset using AMP
          Model
          NVIDIA Deep Learning Examples
          NVIDIA Deep Learning Examples
          BART PyT checkpoint (Summarization, XSum)
          BART PyT checkpoint for summarization on XSum dataset
            Model
            NVIDIA Deep Learning Examples
            NVIDIA Deep Learning Examples
            Bert Large checkpoint (TensorFlow2, Pretraining AMP, LAMB)
            Bert Large TensorFlow2 checkpoint pretrained using AMP and LAMB optimizer
              Model