Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs; Sukmin Yun et al MAVIS: Mathematical Visual Instruction Tuning; Renrui Zhang et al MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions; Xuan Ju et al On Pre-training ...
Using NVIDIA NeMo Framework and NVIDIA Hopper GPUs NVIDIA was able to scale to 11,616 H100 GPUs and achieve near-linear performance scaling on LLM pretraining. NVIDIA also achieved the highest LLM fine-tuning performance and raised the bar for text-to-image training. ...
In addition, we review the recent development of statistical inference based on multiple regression models and the advancement of large-scale multiple testing for high-dimensional regression. The R package SIHR has implemented some of the high-dimensional inference methods discussed in this paper. This...
This is especially important in the context of large-scale IoT systems, such as in the smart city domain. In this article, we present LEONORE, an infrastructure toolset that provides elastic provisioning of application components on resource-constrained and heterogeneous edge devices in large-scale ...
Still, Hive is an ideal express-entry into the large-scale distributed data processing world of Hadoop. All the ease of SQL with all the power of Hadoop — sounds good to me. Thanks to Facebook engineers Joydeep Sen Sarma and Ashish Thusoo for their assistance with this article. Related ...
cases that require more than one framework, such as web-supervised learning, search engine creation, and many others. It can also train and evaluate models on single-node, multi-node, and elastically resizable clusters of computers, so developers can scale up their work without wasting resources...
The choice of the hydrodynamic scale parameter, α, at least in the range of inspection, has little effect on the simulated dispersion relations. This will prove helpful in robust application of this framework to other membrane models and across different scales. While the Full HI model best ...
we decided to use a Ray cluster to convert our raw text and create the embeddings.Rayis an open source unified compute framework that enables ML engineers and Python developers to scale Python applications and accelerate ML workloads. Our cluster consisted of 5 g4dn.12xlargeAmazon Elastic Compute...
Snpnet - Efficient Lasso Solver for Large-scale SNP Data License: GPL-2 References: Junyang Qian, Yosuke Tanigawa, Wenfei Du, Matthew Aguirre, Robert Tibshirani, Manuel A. Rivas, and Trevor Hastie. A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with a...
Deepcrowd: A deep model for large-scale citywide crowd density and flow prediction Urbanfm: Inferring fine-grained urban flows Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction Deepurbanevent: A system for predicting citywide crowd dynamics at big events Promptst:...