… Use examples for fine-tuning the models with your own data and the QCalEval benchmark and data to test model effectiveness. Ising Calibration Run the Ising Calibration 1 in an agentic workflow with our example on GitHub. Evaluate your own models with our QCalEval benchmark dataset. …
… Explore NCore Data Standard for Sensor Data Reconstruction Reconstruct sensor data using consistent data representations. Physical AI Open Datasets for Reconstructed Data Kick-start your rendering pipelines with reconstructed data, openly available on the NVIDIA Physical AI Open Datasets collection. …
… Solve the Training Data Challenge With the Physical AI Data Factory Learn how to build a training data pipeline with your own video or image data. …
… We show the local training code on the left and the federated version on the right, highlighting: import, flare.init , receive , send . train.py train.py import torch import torchvision import torchvision.transforms as transforms from model import Net batch size = 4 epochs = 1 lr = 0.01 model = Net… …
… Nemotron Omni Datasets Multimodal data extending the Nemotron training pipeline beyond text to image, video, and speech. ~127B tokens of cross-modal pretraining data and ~124M curated post-training examples for document reasoning, computer use, and long-horizon workflows. …
… NVDEC helps remove these bottlenecks and together with NVENC enhances data curation workflows for building high-quality video training datasets. …
… Please report security vulnerabilities or NVIDIA AI Concerns here .
… Please report security vulnerabilities or NVIDIA AI Concerns here .
… Nemotron 3 Super—with open weights, open training data, and open development recipes—is ideal for software development, deep research, cybersecurity, and the financial services industry. …
… However, there are others such as: Training data poisoning: Injecting tainted data into datasets used for fine-tuning or training models. …