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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
BioBERTLargeCasedForNeMo
NVIDIA
BioBERT-large cased model checkpoint for NeMo.
Model
Text Classification Notebook
NVIDIA
End to End sample workflow for Text Classification starting with training in TAO Toolkit and deployment using Riva.
Resource
BertLargeUncasedForNemo
NVIDIA
BERT Large Model trained with NeMo on uncased Wikipedia and Bookcorpus on a sequence length 512.
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
Punctuation En Bert
NVIDIA
Punctuation and Capitalization model with BERT
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
BioMegatron345mUncasedSQuADv1
NVIDIA
BioMegatron 345M uncased model for Question Answering finetuned with NeMo on SQuAD v1.1 dataset.
Model
NER En Bert
NVIDIA
Named Entity Recognition model with BERT
Model
BertBaseUncasedSQuADv1
NVIDIA
BERT Base Uncased model for Question Answering finetuned with NeMo on SQuAD v1.1 dataset.
Model
Joint Intent and Slot Classification DistilBert
NVIDIA
Intent and Slot classification of the queries for the misty bot with DistilBert model trained on weather, smalltalk and POI (places of interest) data.
Model
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