Search Results for "source code claude code" - Page 58
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Showing 2475 open source projects for "source code claude code"
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Knock Knock
Get notified when your training ends
Knock Knock is a lightweight Python utility created by the Hugging Face team that allows developers to receive notifications when long-running machine learning tasks finish or fail. Training deep learning models often takes hours or even days, making it inconvenient for engineers to constantly monitor progress manually. The library solves this problem by adding simple decorators or command-line commands that automatically send notifications when a process completes or crashes. These alerts... -
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TensorNets
High level network definitions with pre-trained weights in TensorFlow
High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 >= TF >= 1.4.0). Applicability. Many people already have their own ML workflows and want to put a new model on their workflows. TensorNets can be easily plugged together because it is designed as simple functional interfaces without custom classes. Manageability. Models are written in tf.contrib.layers, which is lightweight like PyTorch and Keras, and allows for ease of accessibility to every weight and... -
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PyZgoubi is an interface to the Zgoubi particle tracking code written in python. It aims to ease the use of Zgoubi by providing a simple interface to create beam line elements and particles, and to automate running and analysing of simulations.
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HDL Checker
Repurposing existing HDL tools to help writing better code
HDL Checker is a language server that wraps VHDL/Verilg/SystemVerilog tools that aims to reduce the boilerplate code needed to set things up. It supports Language Server Protocol or a custom HTTP interface; can infer the library VHDL files likely to belong to, besides working out mixed language dependencies, compilation order, interpreting some compiler messages and providing some (limited) static checks. Notice that currently, the unused reports has caveats, namely declarations with the... -
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stage0
A set of minimal dependency bootstrap binaries
This is a set of manually created hex programs in a Cthulhu Path to madness fashion. Which only have the goal of creating a bootstrapping path to a C compiler capable of compiling GCC, with only the explicit requirement of a single 1 KByte binary or less. Additionally, all code must be able to be understood by 70% of the population of programmers. If the code can not be understood by that volume, it needs to be altered until it satisfies the above requirement. -
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mssqlproxy
Toolkit aimed to perform lateral movement in restricted environments
mssqlproxy is a toolkit aimed to perform lateral movement in restricted environments through a compromised Microsoft SQL Server via socket reuse. The client requires impacket and sysadmin privileges on the SQL server. The first step is to execute code in the SQL Server process context. As extended stored procedures are going to be deprecated in future versions of MSSQL, we pay attention to Microsoft recommendations and thus, use CLR assemblies instead. -
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PixelCNN
Code for the paper "PixelCNN++: A PixelCNN Implementation..."
PixelCNN is the official implementation from OpenAI of the autoregressive generative model described in the paper Conditional Image Generation with PixelCNN Decoders. It provides code for training and evaluating PixelCNN models on image datasets, focusing on conditional image modeling where pixels are generated sequentially based on the values of previously generated pixels. The repository demonstrates how to apply masked convolutions to enforce autoregressive dependencies and achieve... -
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FuzzyWuzzy
Fuzzy string matching in Python
We’ve made it our mission to pull in event tickets from every corner of the internet, showing you them all on the same screen so you can compare them and get to your game/concert/show as quickly as possible. Of course, a big problem with most corners of the internet is labeling. One of our most consistently frustrating issues is trying to figure out whether two ticket listings are for the same real-life event (that is, without enlisting the help of our army of interns). To pick an example... -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments... -
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QRCode-Generator
Application for QR Code generation.
This is a minimalistic application to generate QR Code. Enter the data and easily convert the data to QR Code. -
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CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic... -
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textgenrnn
Easily train your own text-generating neural network
With textgenrnn you can easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code. A modern neural network architecture that utilizes new techniques as attention-weighting and skip-embedding to accelerate training and improve model quality. Train on and generate text at either the character-level or word-level. Configure RNN size, the number of RNN layers, and whether to use bidirectional RNNs. Train on any generic input text... -
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Machine Learning with TensorFlow
Accompanying source code for Machine Learning with TensorFlow
Machine Learning with TensorFlow is an open repository containing the source code and practical examples that accompany the book Machine Learning with TensorFlow. The project provides numerous code samples demonstrating how to build machine learning models using the TensorFlow framework. These examples illustrate core machine learning concepts such as regression, classification, clustering, and neural networks through practical implementations. -
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Spinning Up in Deep RL
Educational resource to help anyone learn deep reinforcement learning
Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the... -
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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
TensorFlow Machine Learning Cookbook repository provides practical code examples and educational materials that accompany the book TensorFlow Machine Learning Cookbook. The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization... -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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Python Bible Reading Module
Python Bible Reading Module is an open source python module.
Python Bible Reading Module ( PBRM ) is an open source python module. It's designed in python 3, but should be compatible with python 2 . This module allows you to easily import different versions of the bible into your code. -
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TensorFlow Course
Simple and ready-to-use tutorials for TensorFlow
This repository houses a highly popular (~16k stars) set of TensorFlow tutorials and example code aimed at beginners and intermediate users. It includes Jupyter notebooks and scripts that cover neural network fundamentals, model training, deployment, and more, with support for Google Colab. -
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Miasm
Reverse engineering framework in Python
The Miasm intermediate representation is used for multiple task: emulation through its jitter engine, symbolic execution, DSE, program analysis, but the intermediate representation can be a bit hard to read. We will present in this article new tricks Miasm has learned in 2018. Among them, the SSA/Out-of-SSA transformation, expression propagation and high-level operators can be joined to “lift” Miasm IR to a more human-readable language. We use graphviz to illustrate some graphs. Its layout... -
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v2rayL
v2ray linux GUI
V2Ray is a tool under Project V. Project V includes a series of tools to help you create your own customized network system. And V2Ray belongs to the core one. Simply put, V2Ray is a proxy software similar to Shadowsocks, but has more advantages than Shadowsocks.v2ray linux client, using pyqt5 to write GUI interface, the core is based on v2ray-core (v2ray-linux-64) vmess supports websocket, mKcp, and tcp. There may be some bugs in the current program, but they have not been tested. If you... -
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Flask-GraphQL
Adds GraphQL support to your Flask application
Adds GraphQL support to your Flask application. This will add /graphql endpoint to your app and enable the GraphiQL IDE. If you are using the Schema type of Graphene library, be sure to use the graphql_schema attribute to pass as schema on the GraphQLView view. Otherwise, the GraphQLSchema from graphql-core is the way to go. The GraphQLSchema object that you want the view to execute when it gets a valid request. A value to pass as the context_value to graphql execute function. By default is... -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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Dive-into-DL-TensorFlow2.0
Dive into Deep Learning
This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2... -
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WebExKit
An HTML/CSS/JavaScript editor with preview window
The Web Experimentation Kit allows you to enter HTML, CSS and JavaScript and see the results immediately in a browser frame side-by-side with the editor. If you've seen the W3Schools Tryit Editor, JSFiddle or CodePen then this should be familiar to you. The difference between WebExKit and these other applications is that WebExKit is a stand-alone application that runs on your desktop and it allows you to save (and reload) files to your own disk drive. The editor shows a properly formed... -
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YouTube-8M
Starter code for working with the YouTube-8M dataset
youtube-8m is Google’s open source starter code and reference implementation for training and evaluating machine learning models on the YouTube-8M dataset, one of the largest video understanding datasets publicly released. The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference.
