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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 78 results
    NVIDIA
    NVIDIA
    nemo-rl
    NVIDIA NeMo™ RL accelerates reinforcement learning post-training with high-performance GPU backends, offering scalable GRPO, DPO, SFT, and distillation for multimodal models from single-node experiments to enterprise-scale clusters.
    Container
    NVIDIA
    NVIDIA
    nemo-automodel
    NVIDIA NeMo™ AutoModel accelerates LLM and VLM training and fine‑tuning with PyTorch DTensor‑native SPMD, day‑0 Hugging Face support, and optimized parallelism from single‑ to multi‑node scale.
    Container
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    GPUNet-0 pretrained weights (PyTorch, AMP, ImageNet)
    GPUNet-0 ImageNet pretrained weights
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    GPUNet-P0 pretrained weights (PyTorch, AMP, ImageNet)
    GPUNet-P0 ImageNet pretrained weights
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    GPUNet-D2 pretrained weights (PyTorch, AMP, ImageNet)
    GPUNet-D2 weights pretrained on ImageNet
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    GPUNet-1 pretrained weights (PyTorch, AMP, ImageNet)
    GPUNet-1 ImageNet pretrained weights
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    GPUNet-2 pretrained weights (PyTorch, AMP, ImageNet)
    GPUNet-2 ImageNet pretrained weights
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    GPUNet-D1 pretrained weights (PyTorch, AMP, ImageNet)
    GPUNet-D1 weights pretrained on ImageNet
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    GPUNet-P1 pretrained weights (PyTorch, AMP, ImageNet)
    GPUNet-P1 ImageNet pretrained weights
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    HiFi-GAN PyT checkpoint (22kHz, AMP)
    HiFi-GAN v1 PyTorch checkpoint trained on 8GPU with AMP on LJSpeech-1.1 (22kHz).
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    HiFi-GAN PyT checkpoint (FastPitch ftune, 22kHz, AMP)
    HiFi-GAN v1 PyTorch checkpoint trained on 8GPU with AMP on LJSpeech-1.1 (22kHz), fine-tuned on FastPitch outputs.
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    QuartzNet checkpoint (PyTorch, AMP, LibriSpeech)
    QuartzNet PyTorch checkpoint trained on LibriSpeech (test-other 10.41% WER)
    Model
    NVIDIA
    NVIDIA
    Fine-tuning Flowtron Model
    Fine-tuning and inference the Flowtron model which is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer.
    Resource
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    TFT PyT checkpoint (Base, AMP, Electricity)
    TFT Base PyTorch checkpoint trained with AMP on Electricity dataset
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    Mask R-CNN TensorFlow checkpoint (AMP)
    Mask R-CNN TensorFlow checkpoint trained with AMP
    Model
    NVIDIA
    NVIDIA
    EfficientNet For Tensorflow2
    EfficientNets are a family of image classification models, which achieve state-of-the-art accuracy, being an order-of-magnitude smaller and faster.
    Resource
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    ResNet50 checkpoints (PaddlePaddle, AMP, ImageNet)
    ResNet50 checkpoint trained with AMP on ImageNet
    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 Deep Learning Examples
    NVIDIA Deep Learning Examples
    TFT PyT checkpoint (Base, AMP, Traffic)
    TFT Base PyTorch checkpoint trained with AMP on Traffic dataset
    Model
    NVIDIA Deep Learning Examples
    NVIDIA Deep Learning Examples
    FastPitch checkpoint (PyTorch, AMP, LJSpeech-1.1, 22050Hz)
    FastPitch PyTorch checkpoint trained on LJSpeech-1.1
    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
    Tacotron2 and WaveGlow PyTorch codebase
    PyTorch codebase for training and using Tacotron2 and Waveglow models
    Resource
    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