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  • Displaying 56 results
    Kaldi
    NVIDIA
    Kaldi is an open-source software framework for speech processing.
    Container
    Text Classification with BERT and NeMo
    NVIDIA
    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
    Fine-Tune and Optimize BERT
    NVIDIA
    Jupyter Notebooks for BERT Pre-training, Fine-Tuning and Inference profiling and optimization via TensorFlow, AMP, XLA, DLProf, TF-TRT and Triton.
    Container
    Megatron GPT2 345M
    NVIDIA NeMo
    345M parameter GPT generative Megatron model
    Model
    BertBaseUncasedForNemo
    NVIDIA
    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
    BertLargeUncasedForNemo
    NVIDIA
    BERT Large Model trained with NeMo on uncased Wikipedia and Bookcorpus on a sequence length 512.
    Model
    BioMegatron345mUncasedSQuADv1
    NVIDIA
    BioMegatron 345M uncased model for Question Answering finetuned with NeMo on SQuAD v1.1 dataset.
    Model
    BertBaseUncasedSQuADv1
    NVIDIA
    BERT Base Uncased model for Question Answering finetuned with NeMo on SQuAD v1.1 dataset.
    Model
    BERT PyTorch checkpoint (Dist-4L-288D, SQuAD1, seqLen384, AMP)
    NVIDIA Deep Learning Examples
    BERT Distilled 4L-288D PyTorch checkpoint distilled on SQuAD v1.1 dataset using AMP
    Model
    BioBERTBaseCasedForNeMo
    Nvidia
    Model
    BertBaseCasedForNeMo
    NVIDIA
    BERT Base Model trained with NeMo on cased Wikipedia and BookCorpus on a sequence length of 512.
    Model
    BERT PyTorch checkpoint (Large, SST-2, seqLen128, AMP)
    NVIDIA Deep Learning Examples
    BERT Large PyTorch checkpoint finetuned on GLUE/SST-2 dataset using AMP
    Model
    TRADE - MultiWOZ 2.0 - Dialogue State Tracker
    NVIDIA
    Checkpoint of TRADE model for dialogue state tracking trained on MultiWOZ 2.0 dataset using NeMo.
    Model
    Bert Large checkpoint (TensorFlow2, AMP, Squad1.1, seqLen384)
    NVIDIA Deep Learning Examples
    Bert Large TensorFlow2 checkpoint finetuned on Squad1.1 using seqLen=384
    Model
    TRADE - MultiWOZ 2.1 - Dialogue State Tracker
    NVIDIA
    Checkpoint of TRADE model for dialogue state tracking trained on MultiWOZ 2.1 dataset using NeMo.
    Model
    BERT PaddlePaddle checkpoint (Large, Pretraining, AMP, LAMB)
    NVIDIA Deep Learning Examples
    BERT Large PaddlePaddle checkpoint pretrained with LAMB optimizer using AMP
    Model
    BERT PyTorch checkpoint (Dist-6L-768D, SQuAD1, AMP)
    NVIDIA Deep Learning Examples
    BERT Distilled 6L-768D PyTorch checkpoint distilled on SQuAD v1.1 dataset using AMP
    Model
    BERT PyTorch checkpoint (Base, Pretraining, AMP, LAMB)
    NVIDIA Deep Learning Examples
    BERT Base PyTorch checkpoint pretrained with LAMB optimizer using AMP
    Model
    BERT PyTorch checkpoint (Dist-6L-768D, Pretraining, AMP)
    NVIDIA Deep Learning Examples
    BERT Distilled 6L-768D PyTorch Phase2 checkpoint pretrained using 67K steps on seqLen128 and 6k steps on seqLen512
    Model
    BERT PyTorch checkpoint (Dist-4L-288D, Pretraining, AMP)
    NVIDIA Deep Learning Examples
    BERT Distilled 4L-288D PyTorch checkpoint distilled on pretraining dataset using AMP
    Model
    BART PyT checkpoint (Summarization, XSum)
    NVIDIA Deep Learning Examples
    BART PyT checkpoint for summarization on XSum dataset
    Model
    Bert Large checkpoint (TensorFlow2, Pretraining AMP, LAMB)
    NVIDIA Deep Learning Examples
    Bert Large TensorFlow2 checkpoint pretrained using AMP and LAMB optimizer
    Model

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