Structure

A simple vault structure using OP_CTV

This repository demonstrates an implementation of simple, “single-hop” vaultsusing the proposed OP_CHECKTEMPLATEVERIFY opcode. OP_CTV allows the vault strategy to be used without the need to maintain criticalpresigned transaction data for the lifetime of the vault, as in the case of earliervault implementations. This approach is much simpler operationally, since all relevantdata aside from key material can be regenerated algorithmically. This makes vaultingmore practical at any scale. The code included here is intended to be approachable and easy to read, thoughit […]

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Fuzzing

The Python Fuzzer that the world deserves

pip3 install frelatage Current release : 0.0.2 The Python Fuzzer that the world deserves Installation    |    How it works    |    Features    |    Use Frelatage    |    Configuration Frelatage is a coverage-based Python fuzzing library which can be used to fuzz python code. The development of Frelatage was inspired by various other fuzzers, including AFL/AFL++, Atheris and PyFuzzer.The main purpose of the project    

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Download

GUI/CLI Downloader App

NH-DL is (preferably) a GUI utility for downloading from a very special website.Speaking of this website, this is the perfect time for a… DISCLAIMER This tool, that is, NH-DL, is intended for use by adults who are willingly submittingthemself to the possibility that they could potentially view adult (R18) content. NH-DL is (preferably) a GUI, as well as a command-line downloading utility that offersthe ability to download from the website NHentai without an account, and with relative easeby simply typing […]

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Benchmark

A Legal AI Benchmark Dataset from Korean Legal Cases

A Legal AI Benchmark Dataset from Korean Legal Cases by LBox Authors Updates Mar 2022: We release lbox_open_v0.1! How to use the dataset We use datasets library from Hugging Face. # !pip install datasets from datasets import load_dataset # casename classficiation task data_cn = load_dataset(“lbox/lbox_open”, “casename_classification”) # statutes classification task data_st = load_dataset(“lbox/lbox_open”, “statute_classification”) # case summarization task data_summ =

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Python

Counting With Python’s Counter

Counting several repeated objects at once is a common problem in programming. Python offers a bunch of tools and techniques you can use to approach this problem. However, Python’s Counter from collections provides a clean, efficient, and Pythonic solution. This dictionary subclass provides efficient counting capabilities out of the box. Understanding Counter and how to use it efficiently is a convenient skill to have as a Python developer. In this video course, you’ll learn how to: Count several repeated objects […]

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Message

Small VK userbot to substitute some message parts with other message parts, cross or underline text, and add images to a message

WARNING: “substitutions” are just text substitutions, while “attachments” are being added to the current message as attachments Also don’t forget to put your token in token.txt, you know… attachments.json SHOULD NOT BE FILLED MANUALLY!substitutions.json SHOULD BE FILLED MANUALLY! (format: {“pattern”: “substitution”, “pattern”: “substitution”, …}) uline and cross do not depend on any of the configs.If you surround some text with the uline macro, the text surrounded will be underlined,if you surround some text with the cross macro, the text surrounded […]

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Converter

Convert scikit-learn models to PyTorch modules

sk2torch converts scikit-learn models into PyTorch modules that can be tuned with backpropagation and even compiled as TorchScript. Problems solved by this project: scikit-learn cannot perform inference on a GPU. Models like SVMs have a lot to gain from fast GPU primitives, and converting the models to PyTorch gives immediate access to these primitives. While scikit-learn supports serialization through pickle, saved models are not reproducible across versions of the library. On the other hand, TorchScript provides a convenient, safe way […]

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Images

Self-Distilled Internet Photos (SDIP) Dataset

Self-Distilled Internet Photos (SDIP) is a multi-domain image dataset. The dataset consists of Self-Distilled Flickr (SD-Flickr) and Self-Distilled LSUN (SD-LSUN) that were crawled from Flickr and LSUN dataset, respectively, and then curated using the method described in our Self-Distilled StyleGAN paper: Self-Distilled StyleGAN: Towards Generation from Internet PhotosRon Mokady, Michal Yarom, Omer Tov, Oran Lang, Daniel Cohen-Or, Tali Dekel, Michal Irani, Inbar Mosserihttps://arxiv.org/abs/2202.12211 Overview StyleGAN’s fascinating generative and editing abilities are limited to structurally aligned and well-curated datasets. It does […]

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Telegram

Go live easily and stream videos in Telegram channels

A bot for streaming in Telegram RTMP streams. Get Started Use a Cloud Platform Manually Prerequisites Configure In order to configure the bot, you have to set the following environmental variables: APP_HASH APP_ID BOT_TOKEN RTMP_KEY RTMP_URL Or put them in a .env in the root. Install Run poetry run python -m trtmp Commands Currently, TRTMP has 2 commands. To request more features and commands, talk to usin @CallsMusicChat. Note: Commands are triggered with the “/” prefix. stream As you may […]

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