Estimate and track object poses with the NVIDIA TAO FoundationPose model Open vocabulary object detection with NVIDIA Grounding-DINO Use text prompts for auto-labeling with NVIDIA TAO Visualize model training with TensorBoard Developer blogs Webinars Support Information TAO Launcher Running the...
TAO 5.5.0 introduces finetuning and inference support for Open Vocabulary Grounded Object Detection and Instance Segmentation through the GroundingDINO and Mask GroundingDINO. GitHub repository. NVIDIA also includes two new inference applications as part of the TAO. A gradio app to try out zero-shot...
The general idea of Meta-NLG is to train a base model fθ with high-resource source tasks, followed by fine-tuning on low-resource target tasks during meta-training, as expressed in Eq. (6.14), where θS denotes a pretrained initialization parameter θs with DA-utterance pairs DS = {(...
This chapter contains an overview of Sun Embedded WorkshopTM."Introduction to Sun Embedded Workshop" provides a high-level overview of Sun Embedded Workshop. "Features and Benefits" describes the key features of the product and why they are useful to you. "Operating System Components" provides ...
We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COVID include the construction of a pandemic search test collection and the evaluation of IR methods for COVID-19....
Intel Technology Journal Q1, 1998 Preface Lin Chao Editor Intel Technology Journal This Q1'98 issue of the Intel Technology Journal focuses on Intel's tera-scale supercomputer and research on multithreading software libraries for applications. On June 11, 1997, the Intel supercomputer, containing ...
Microfluidics deals with the transport of minute volumes of fluid (typically, sub-nanoliter) through channels having at least one of three dimensions of the order of micrometer [1]. Though, initially microfluidics stemmed out of two distant fields, namely, analytical chemistry [2] and microfabricat...
the authors implemented a mechanism to change the dimension of the input data to degrade individual speaker features in the spectrogram. This implementation reduces the need for fine-tuning the dimensions of the bottleneck in the linguistic extractor. The authors then projected the latent representation...
These loss functions are specifically designed to be used when distilling the knowledge from one model into another. For example, when finetuning a small model to behave more like a larger & stronger one, or when finetuning a model to become multi-lingual. TextsLabelsAppropriate Loss Functions ...
The text-2-image example is just a basic tutorial to highlight the underlying usage of the Diffusers library. It also provides multiple other functionalities including Image-2-image generation, inpainting, outpainting, and control-nets. In addition, they provide fine control over each module in th...