NGC | Catalog
Welcome Guest
CatalogModels
Many AI applications have common needs: classification, object detection, language translation, text-to-speech, recommender engines, sentiment analysis, and more. When developing applications with these capabilities, it is much faster to start with a model that is pre-trained and then tune it for a specific use case. The NGC catalog offers pre-trained models for a variety of common AI tasks that are optimized for NVIDIA Tensor Core GPUs, and can be easily re-trained by updating just a few layers, saving valuable time.
Sort: Last Modified
Logo for Riva TTS English Normalization Grammar
Riva TTS English Normalization Grammar
Model
Base English grammar
RMIR Conformer Hindi (hi-IN) Streaming Througput
Model
Conformer trained on Riva ASR-set 1.0
RMIR Conformer Hindi (hi-IN) Streaming Throughput
Model
Conformer trained on Riva ASR-set 1.0 with 3 gram LM
RMIR Conformer Hindi (hi-IN) Streaming
Model
Conformer trained on Riva ASR-set 1.0 with 3 gram LM
RMIR Conformer Hindi (hi-IN) Streaming
Model
Conformer trained on Riva ASR-set 1.0 with 3 gram LM
RMIR Conformer Hindi (hi-IN) Offline
Model
Conformer trained on Riva ASR-set 1.0
RMIR Conformer Hindi (hi-IN) Offline
Model
Conformer trained on Riva ASR-set 1.0 with 3 gram LM
Logo for RIVA Punctuation and Capitalization for Mandarin
RIVA Punctuation and Capitalization for Mandarin
Model
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.
Logo for RIVA Conformer ASR Hindi
RIVA Conformer ASR Hindi
Model
Hindi Conformer ASR model trained on ASR set 1.0
Logo for FinMegatron345m-gpt2-bpe
FinMegatron345m-gpt2-bpe
Model
FSI : Financial Megatron GPT2 345m parameters model with BPE tokenizer, gpt vocabulary and merge file, pre-trained on subsets of CC-100 text corpus.
Logo for FinMegatron345m-uncased
FinMegatron345m-uncased
Model
FSI : Financial Megatron 345m parameters model with bert vocabulary (28k size) uncased, pre-trained on subsets of CC-100 text corpus.
Logo for STT En ContextNet 1024
STT En ContextNet 1024
Model
ContextNet-1024 model for English Automatic Speech Recognition, trained on NeMo ASRSET
Logo for Megatron GPT2 345M
Megatron GPT2 345M
Model
345M parameter GPT generative Megatron model
Logo for Megatron-BERT 345M Cased
Megatron-BERT 345M Cased
Model
345M parameter BERT Megatron model with cased vocab
Logo for Megatron-BERT 345M Uncased
Megatron-BERT 345M Uncased
Model
345M parameter BERT Megatron model with uncased vocab
Logo for BioMegatron345mCased
BioMegatron345mCased
Model
Megatron pretrained on cased biomedical dataset PubMed with 345 million parameters.
Logo for BioMegatron345mUncased
BioMegatron345mUncased
Model
Megatron pretrained on uncased biomedical dataset PubMed with 345 million parameters.
Logo for BioMegatron345m-biovocab-50k-uncased
BioMegatron345m-biovocab-50k-uncased
Model
Megatron 345m parameters model with biomedical vocabulary (50k size) uncased, pre-trained on PubMed biomedical text corpus.
Logo for BioMegatron345m-biovocab-30k-uncased
BioMegatron345m-biovocab-30k-uncased
Model
Megatron 345m parameters model with biomedical vocabulary (30k size) uncased, pre-trained on PubMed biomedical text corpus.
Logo for BioMegatron345m-biovocab-50k-cased
BioMegatron345m-biovocab-50k-cased
Model
Megatron 345m parameters model with biomedical vocabulary (50k size) cased, pre-trained on PubMed biomedical text corpus.
Logo for BioMegatron345m-biovocab-30k-cased
BioMegatron345m-biovocab-30k-cased
Model
Megatron 345m parameters model with biomedical vocabulary (30k size) cased, pre-trained on PubMed biomedical text corpus.
Logo for Action Recognition Net
Action Recognition Net
Model
5 class action recognition network to recognize what people do in an image.
Logo for Joint Intent and Slot Classification Misty Bert
Joint Intent and Slot Classification Misty Bert
Model
Intent and Slot classification of the queries for the misty bot with BERT model trained on weather, smalltalk and POI (places of interest) data.
Logo for GPUNet-P1 pretrained weights (PyTorch, AMP, ImageNet)
GPUNet-P1 pretrained weights (PyTorch, AMP, ImageNet)
Model
GPUNet-P1 ImageNet pretrained weights
Logo for GPUNet-P0 pretrained weights (PyTorch, AMP, ImageNet)
GPUNet-P0 pretrained weights (PyTorch, AMP, ImageNet)
Model
GPUNet-P0 ImageNet pretrained weights