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Showing 6 open source projects for "single user"
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99.99% Uptime for MySQL and PostgreSQL on Google CloudCloud SQL Enterprise Plus gives you a 99.99% availability SLA with near-zero downtime maintenance—typically under 10 seconds. Get 2x better read/write performance, intelligent data caching, and 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server with built-in vector search for gen AI apps. New customers get $300 in free credit.
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Petastorm
Petastorm library enables single machine or distributed training
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
...These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
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PyTorch/XLA
Enabling PyTorch on Google TPU
...This is our recommedned way of running PyTorch/XLA on Cloud TPU. Please check out our Cloud TPU VM User Guide. Cloud TPU VM is currently on general availability and provides direct access to the TPU host. The recommended setup for running distributed training on TPU Pods uses the pairing of Compute VM Instance Groups and TPU Pods. Each of the Compute VM in the instance group drives 8 cores on the TPU Pod. -
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Datasets
Hub of ready-to-use datasets for ML models
...There are currently over 2658 datasets, and more than 34 metrics available. Datasets naturally frees the user from RAM memory limitation, all datasets are memory-mapped using an efficient zero-serialization cost backend (Apache Arrow). Smart caching: never wait for your data to process several times. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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X-DeepLearning
An industrial deep learning framework for high-dimension sparse data
X-DeepLearning (XDL for short) is a complete set of deep optimization solutions for high-dimensional sparse data scenarios (such as advertising/recommendation/search, etc.). XDL version 1.2 has been released recently. Performance optimization for large batch/low concurrency scenarios, 50-100% performance improvement in such scenarios. Storage and communication optimization, parameters are automatically allocated globally without manual intervention, and requests are merged to completely...
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