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Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major...

Ultroid, a pluggable telegram userbot, made in python using Telethon! Ultroid has been written from scratch, making it more stable and less crashes. Ultroid warns you when you try to install/execute dangerous stuff (people nowadays make plugins to hack user accounts, Ultroid is safe). Unlike many others userbots that are being suspended by Heroku, Ultroid doesn't get suspended. Ultroid has been written from scratch, making it more stable and less of crashes. Error handling been done in the best way possible, such that the bot doesn't crash and stop all of a sudden. ...

Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the...

This repository aims to provide simple and ready-to-use tutorials for TensorFlow. The explanations are present in the wiki associated with this repository. There are different motivations for this open source project. TensorFlow (as we write this document) is one of / the best deep learning frameworks available. The question that should be asked is why has this repository been created when there are so many other tutorials about TensorFlow available on the web? Deep Learning is in very high...

...The migration of files to the cloud happens transparently and securely, with no disruption to existing applications or infrastructure. The SDK uses on-premises storage as Tier 0 (hot storage) and cloud storage as Tier 1 (cold storage). Cooler or less frequently accessed data is automatically moved to cloud storage, freeing up local storage capacity. Your applications can continue to access all files as if they reside locally—no changes to your code or workflow are required.