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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 66 results
    Voice Demo for Jetson/L4T
    NVIDIA
    ASR + BERT QA interactive chatbot demo for Jetson
    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
    BERT for TensorFlow Jupyter Notebook
    NVIDIA
    Jupyter Notebook example for Question Answering with BERT for TensorFlow
    Resource
    DLI NLP Course - Base Environment with NeMo
    NVIDIA
    Base environment used in the NVIDIA NeMo projects of the NVIDIA Deep Learning Institute (DLI) course, "Building Transformer-Based Natural Language Processing Applications". This container also includes a "Next Steps" project.
    Container
    Domain Classification English Bert
    NVIDIA
    Domain classification of the query for weather chat bot.
    Model
    BERT on Google Cloud AI Platform
    NVIDIA
    Fine-tune a pre-trained BERT model with the SQuAD dataset, optimize for inference using TensorRT and deploy with Triton Inference Server on Google Cloud AI Platform using Custom Containers
    Resource
    Bertlargeuncased
    NVIDIA
    BERT Large Uncased trained on English Wikipedia and BookCorpus
    Model
    BioMegatron345mUncased
    NVIDIA
    Megatron pretrained on uncased biomedical dataset PubMed with 345 million parameters.
    Model
    Bertbaseuncased
    NVIDIA
    BERT Base Uncased trained on English Wikipedia and BookCorpus
    Model
    Question Answering Notebook
    NVIDIA
    End to End workflow for question answering starting with training in TAO Toolkit and deployment using Riva.
    Resource
    RIVA Punctuation and Capitalization for English
    NVIDIA
    For each word in the input text, the model: 1) predicts a punctuation mark that should follow the word (if any), the model supports commas, periods and question marks) and 2) predicts if the word should be capitalized or not.
    Model
    Text Classification Notebook
    NVIDIA
    End to End sample workflow for Text Classification starting with training in TAO Toolkit and deployment using Riva.
    Resource
    BertBaseUncasedForNemo
    NVIDIA
    BERT Base Model trained on uncased Wikipedia and BookCorpus dataset on a sequence length of 512.
    Model
    BioBERTLargeCasedForNeMo
    NVIDIA
    BioBERT-large cased model checkpoint for NeMo.
    Model
    Punctuation En Bert
    NVIDIA
    Punctuation and Capitalization model with BERT
    Model
    BioMegatron345mCased
    —
    Megatron pretrained on cased biomedical dataset PubMed with 345 million parameters.
    Model
    RIVA Punctuation
    NVIDIA
    For each word in the input text, the model: 1) predicts a punctuation mark that should follow the word (if any), the model supports commas, periods and question marks) and 2) predicts if the word should be capitalized or not.
    Model
    BertLargeUncasedForNemo
    NVIDIA
    BERT Large Model trained with NeMo on uncased Wikipedia and Bookcorpus on a sequence length 512.
    Model
    NER En Bert
    NVIDIA
    Named Entity Recognition model with BERT
    Model
    BioMegatron345mUncasedSQuADv1
    NVIDIA
    BioMegatron 345M uncased model for Question Answering finetuned with NeMo on SQuAD v1.1 dataset.
    Model
    Question Answering SQUAD2.0 Bert
    NVIDIA
    Question Answering Bert Base uncased model for extractive question answering on any provided content.
    Model
    Joint Intent and Slot Classification Bert
    NVIDIA
    Intent and Slot classification of the qeuries for the weather chat bot (trained on weather chat bot data).
    Model

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