Search Results for "what" - Page 9
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Showing 407 open source projects for "what"
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onnxt5
Summarization, translation, sentiment-analysis, text-generation, etc.
...Run any of the T5 trained tasks in a line (translation, summarization, sentiment analysis, completion, generation) Export your own T5 models to ONNX easily. Utility functions to generate what you need quickly. Up to 4X speedup compared to PyTorch execution for smaller contexts. -
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Soma-direct
System Omnichannel Marketing Analysis
...With Soma, you can combine data from multiple systems and channels in the profile joining process. Interactions and behaviors registered as a part of a unique user create and show what a Customer Journey looks like. The data is subjected to an analysis process which enables the examination of the significance of individual touchpoints for the purchasing process. -
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Text2Video
Software tool that converts text to video for more engaging experience
...I started this project because during this semester, I have been given many reading assignments and I felt frustration in reading long text. For me, it was very time and energy-consuming to learn something through reading. So I imagined, "What if there was a tool that turns text into something more engaging such as a video, wouldn't it improve my learning experience?" I created a prototype web application that takes text as an input and generates a video as an output. I plan to further work on the project targeting young college students who are aged between 18 to 23 because they tend to prefer learning through videos over books based on the survey I found. ... -
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OpenFrames
Real-time interactive 3D graphics API for scientific simulations
...Get it at https://github.com/ravidavi/OpenFrames/wiki OpenFrames is an Application Programming Interface (API) that allows developers to provides the ability to add interactive 3D graphics to any scientific simulation. A simulation developer can use OpenFrames to specify what they want to visualize, without having to know any details of computer graphics programming. OpenFrames is currently used by three NASA programs: Copernicus (NASA JSC), the General Mission Analysis Tool (GMAT, NASA GSFC), and a Virtual Reality exploration tool (NASA GSFC). -
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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Xwintrack
Track key and mouse input to X windows
...Keytracker, mousetracker, movement tracker Allows tracking of keys, mouse buttons and mouse position in a selected X window or globally. It performs no logging of its own, it tracks and reports what is occurring, allowing the programmer to do want they will with the information. Key tracking / logging Mouse tracking / logging Hot keys Hot mouse buttons / keys Many xdotool function replacement commands -
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SentEval
A python tool for evaluating the quality of sentence embeddings
...It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic structure. Datasets are wrapped with unified preprocessing and metrics so results are comparable across papers and implementations. Because the interface is minimal, researchers can plug in encoders from any framework or language model and obtain a broad evaluation with little glue code. ... -
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Crossfire-Extended-Release
A roguelike, contains binaries and source packages for
...In the source package python 2.0 and 2.4 are included, so you can run the pyscripts (which are from an earlier age!) And the gtk2 client and CFPlus perl client and libs. The 64bit binaries pkgs have everything set up for you, just set the permissions to what user will run the game. gcfclient2 crossedit crossfire What more could you want from a 2d RpG? -
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Howdy For Linux
Windows Hello style facial authentication for Linux
Howdy provides Windows Hello™ style authentication for Linux. Use your built-in IR emitters and camera in combination with facial recognition to prove who you are. Using the central authentication system (PAM), works everywhere you would otherwise need your password: Login, lock screen, sudo, su, etc. -
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vim-visual-multi
Multiple cursors plugin for vim/neovim
vim-visual-multi is a plugin that brings multi-cursor functionality to Vim and Neovim similar to what many modern editors provide. Instead of only using Vim’s traditional visual or block modes, this plugin allows you to set up multiple cursors (and multiple selection spots) and perform edits simultaneously in several places at once. You can add cursors by selecting words or using vertical cursor movements, then enter insert or normal mode and your commands are replicated across all active cursors. ... -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Delta ML
Deep learning based natural language and speech processing platform
...DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. It helps you to train, develop, and deploy NLP and/or speech models. Use configuration files to easily tune parameters and network structures. What you see in training is what you get in serving: all data processing and features extraction are integrated into a model graph. Text classification, named entity recognition, question and answering, text summarization, etc. Uniform I/O interfaces and no changes for new models. -
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macOS Simple KVM
Tools to set up a quick macOS VM in QEMU, accelerated by KVM
macOS-Simple-KVM is a project that provides scripts and configuration files to easily set up and run macOS in a virtual machine using QEMU and KVM. It simplifies what is typically a complex process by offering a straightforward approach to creating a macOS VM on Linux systems with hardware virtualization support. The repository includes tools for preparing installation media, configuring virtual hardware, and managing VM launch scripts. By using KVM acceleration, the virtual machine runs with near-native performance, making it useful for testing, development, or personal experimentation. ... -
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Rdbtools
Parse Redis dump.rdb files, Analyze Memory, and Export Data to JSON
...The parser generates events similar to an XML sax parser and is very efficient memory-wise. Rdbtools is written in Python, though there are similar projects in other languages. Every run of RDB Tool requires to specify a command to indicate what should be done with the parsed RDB data. Valid commands are JSON, diff, justkeys, justkeyvals and protocol. The JSON command output is UTF-8 encoded JSON. By default, the callback try to parse RDB data using UTF-8 and escape non 'ASCII printable' characters with the \U notation, or non-UTF-8 parsable bytes with \x. Attempting to decode RDB data can lead to binary data corruption, this can be avoided by using the --escape raw option. ... -
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Brand new cheatsheets and handouts
Matplotlib 3.1 cheat sheet
...For practitioners working on data-heavy projects, dashboards, or research code where plotting is frequent, it helps speed up development by reducing context-switching and documentation navigation overhead. It is especially useful when you know roughly what you want (e.g. “I need a scatter + histogram marginal plot”) but don’t remember the exact Matplotlib call. -
14
DETR
End-to-end object detection with transformers
...We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture. Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. ... -
15
mongoaudit
A powerful MongoDB auditing and pentesting tool
...It is widely known that there are quite a few holes in MongoDB's default configuration settings. This fact, combined with abundant lazy system administrators and developers, has led to what the press has called the MongoDB apocalypse. mongoaudit not only detects misconfigurations, known vulnerabilities and bugs but also gives you advice on how to fix them, recommends best practices and teaches you how to DevOp like a pro! MongoDB listens on a port different to default one. Server only accepts connections from whitelisted hosts / networks. ... -
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PyReminder
PyReminder will remind you of what you need at the indicated interval
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Hénon map browser
Program for exploring the Hénon attractor
A Python program for exploring the Hénon attractor. For an explanation of what the Hénon attractor is please see Wikipedia (http://en.wikipedia.org/wiki/H%C3%A9non_map). With this program you can draw the Hénon attractor and interact with it in various ways. You can zoom in by selecting an area, vary the Henon parameters manually and even make animations with them. The functionality is demonstrated in a Youtube video. -
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Aida Lib
Aida is a language agnostic library for text generation
...A variable can hold numbers (e.g. float, int) or strings. You can create branches and complex logic with Branch. The context, represented by the class Ctx, is useful to create rules that depends on what has been written before. Each object or literal that is passed to Aida is remembered by the context. Creating a reference expression is a common use-case, so we have a helper function called create_ref. You can compose operations on your text with some handy operators. -
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Snips NLU
Snips Python library to extract meaning from text
...It’s the library that powers the NLU engine used in the Snips Console that you can use to create awesome and private-by-design voice assistants. The exact output is a bit richer, the point here is to give a glimpse on what kind of information can be extracted. Behind every chatbot and voice assistant lies a common piece of technology: Natural Language Understanding (NLU). Anytime a user interacts with an AI using natural language, their words need to be translated into a machine-readable description of what they meant. The NLU engine first detects what the intention of the user is (a.k.a. intent), then extracts the parameters (called slots) of the query. ... -
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A Machine Learning Course with Python
A course about machine learning with Python
...The purpose of this project is to provide the most important aspects of Machine Learning by presenting a series of simple and yet comprehensive tutorials using Python. In this project, we built our tutorials using many different well-known Machine Learning frameworks such as Scikit-learn. In this project you will learn what is the definition of Machine Learning? When it started and what is the trending evolution? What are the Machine Learning categories and subcategories? What are the mostly used Machine Learning algorithms and how to implement them? -
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wtfpython
Exploring and understanding Python through surprising snippets
Python, being a beautifully designed high-level and interpreter-based programming language, provides us with many features for the programmer's comfort. But sometimes, the outcomes of a Python snippet may not seem obvious at first sight. Here's a fun project attempting to explain what exactly is happening under the hood for some counter-intuitive snippets and lesser-known features in Python. While some of the examples you see below may not be WTFs in the truest sense, but they'll reveal some of the interesting parts of Python that you might be unaware of. I find it a nice way to learn the internals of a programming language, and I believe that you'll find it interesting too! ... -
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Jarvis
Personal Assistant for Linux and macOS
...In order to start Jarvis just clone this repository and run python installer. Run Jarvis from anywhere by command jarvis. You can start by typing help within the Jarvis command line to check what Jarvis can do for you. Plugins may be modified using the decorators @alias, @require and @complete. These special decorators may be used in any order or several times.Not all plugins are compatible with every system. To specify compatibility constraints, use the require-feature. -
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gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
...You can play around with all four GPT-2 models in less than five lines of code. Install client via pip. The generation options are highly flexible. You can mix and match based on what kind of text you need generated, be it multiple chunks or one at a time with prompts. -
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Spotlight
Deep recommender models using PyTorch
...For example, generate_sequential generates a Markov-chain-derived interaction dataset, where the next item a user chooses is a function of their previous interactions. Recommendations can be seen as a sequence prediction task: given the items a user has interacted with in the past, what will be the next item they will interact with? Spotlight provides a range of models. -
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nonechucks
Deal with bad samples in your dataset dynamically
nonechucks is a library that provides wrappers for PyTorch's datasets, samplers and transforms to allow for dropping unwanted or invalid samples dynamically. What if you have a dataset of 1000s of images, out of which a few dozen images are unreadable because the image files are corrupted? Or what if your dataset is a folder full of scanned PDFs that you have to OCRize, and then run a language detector on the resulting text, because you want only the ones that are in English? Or maybe you have an AlternateIndexSampler, and you want to be able to move to dataset[6] after dataset[4] fails while attempting to load! ...
