Search Results for "hibernate-distribution"
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Showing 342 open source projects for "hibernate-distribution"
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ShredOS
Shredos Disk Eraser 64 bit for all Intel 64 bit processors
For all Intel and compatible 64 & 32 bit processors. ShredOS is a USB bootable (BIOS or UEFI) small linux distribution with the sole purpose of securely erasing the entire contents of your disks using the program nwipe. If you are familiar with dwipe from DBAN then you will feel right at home with ShredOS and nwipe. What are the advantages of nwipe over dwipe/DBAN? Well as everybody probably knows, DBAN development stopped in 2015 which means it has not received any further bug fixes or support for new hardware since that date. ... -
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brython
Implementation of Python 3 running in the browser
...The most simple way to get started, without anything to install, is to use the distribution available online through jsDelivr. -
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AutoPkg
Automating packaging and software distribution on macOS
AutoPkg is a system that automatically prepares software for distribution to managed clients. Recipes allow you to specify a series of simple actions which combined together can perform complex tasks, similar to Automator workflows or Unix pipes. -
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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
...The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution, Bayesian networks can be dropped into a mixture just as easily as a normal distribution, and hidden Markov models can be dropped into Bayes classifiers to make a classifier over sequences. Together, these two design choices enable a flexibility not seen in any other probabilistic modeling package. -
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Panda-Helper
Panda-Helper: Data profiling utility for Pandas DataFrames and Series
Panda-Helper is a simple data-profiling utility for Pandas DataFrames and Series. Assess data quality and usefulness with minimal effort. Quickly perform initial data exploration, so you can move on to more in-depth analysis. -
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OpenCLIP
An open source implementation of CLIP
The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when trained on the same subset of YFCC. ... -
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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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MoneyPrinterTurbo
Generate short videos with one click using AI LLM
...By providing a topic or keyword, the system automatically creates video scripts, sources relevant media assets, adds subtitles, and incorporates background music, resulting in a polished video ready for distribution. -
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Otter-Grader
A Python and R autograding solution
Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope. -
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PyMongo
PyMongo - the Official MongoDB Python driver
The PyMongo distribution contains tools for interacting with MongoDB database from Python. The bson package is an implementation of the BSON format for Python. The pymongo package is a native Python driver for MongoDB. The gridfs package is a gridfs implementation on top of pymongo. -
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Kitten TTS
State-of-the-art TTS model under 25MB
KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis. -
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Encord Active
The toolkit to test, validate, and evaluate your models and surface
...Use the intuitive UI to explore your data or access all the functionalities programmatically. Discover errors, outliers, and edge-cases within your data - all in one open source toolkit. Get a high level overview of your data distribution, explore it by customizable quality metrics, and discover any anomalies. Use powerful similarity search to find more examples of edge-cases or outliers. -
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troposphere
Python library to create AWS CloudFormation descriptions
The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes. -
14
Flow Matching
A PyTorch library for implementing flow matching algorithms
flow_matching is a PyTorch library implementing flow matching algorithms in both continuous and discrete settings, enabling generative modeling via matching vector fields rather than diffusion. The underlying idea is to parameterize a flow (a time-dependent vector field) that transports samples from a simple base distribution to a target distribution, and train via matching of flows without requiring score estimation or noisy corruption—this can lead to more efficient or stable generative training. The library supports both continuous-time flows (via differential equations) and discrete-time analogues, giving flexibility in design and tradeoffs. It provides examples across modalities (images, toy 2D distributions) to help users understand how to apply flow matching in practice. ... -
15
Pyxel
A retro game engine for Python
...Using the Pyxel Web Launcher or custom elements for HTML, you can run Pyxel in a web browser without any installation work. Pyxel supports a dedicated application distribution file format (Pyxel application file) that works across platforms. 8 musics that can combine arbitrary sounds. -
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Pyodide
Pyodide is a Python distribution for the browser and Node.js
Pyodide brings the Python runtime to the browser by compiling Python and its scientific libraries to WebAssembly. It allows developers to run Python code directly in web browsers without a server, supporting packages like NumPy, Pandas, and Matplotlib. Pyodide opens up new possibilities for interactive data analysis, scientific computing, and educational tools in web environments, all while integrating seamlessly with JavaScript. -
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Pyro
Deep universal probabilistic programming with Python and PyTorch
...It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable abstractions that make it both agile and maintainable. Lastly, Pyro gives you the flexibility of automation when you want it, and control when you need it. -
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Google Fonts
Font files available from Google Fonts, and a public issue tracker
This is the central GitHub repository for Google Fonts, containing font binaries, metadata, and tools for uploading new typeface families. It serves as the staging area for fonts and follows stringent licensing structures. The top-level directories indicate the license of all files found within them. Subdirectories are named according to the family name of the fonts within. The /catalog subdirectory contains additional metadata, such as profile texts and portrait/avatar images of font... -
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Intelligent stock analysis system
LLM-driven A/H/US stock intelligent analyzer
...It’s designed to produce a daily “decision dashboard” summarizing key insights such as core conclusions, precise entry/exit points, and checklists for potential trades, combining multi-dimensional technical analysis, market sentiment, chip distribution, and real-time price data. The system supports scheduled execution using GitHub Actions, enabling fully automated daily analysis and multi-channel notifications via platforms like Telegram, Enterprise WeChat, Feishu, email, and push services. Under the hood, it integrates multiple AI models (like Gemini and OpenAI-compatible models) and diverse market data sources (including AkShare, Tushare, and YFinance) to synthesize comprehensive reports. -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic... -
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Bottle
bottle.py is a fast and simple micro-framework for python applications
Bottle is a minimalist web framework for building small web applications and APIs in Python. It is distributed as a single file with no external dependencies, making it perfect for rapid development, prototyping, or embedded use. Despite its small size, Bottle supports routing, templates, request handling, and plugin support, offering a full-featured toolkit in an extremely compact package. -
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NGBoost
Natural Gradient Boosting for Probabilistic Prediction
ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn and is designed to be scalable and modular with respect to the choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck. -
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Modoboa
Mail hosting made simple
...It is written in Python 3 and uses the Django, jQuery and Bootstrap frameworks. Follow the evolution of your server traffic thanks to a few builtin graphics: messages distribution per type and average size. Easily use standard protocols like DKIM or DMARC to improve your sender reputation and so make sure your emails will be delivered. Consult your emails everywhere thanks to simple but functional builtin webmail. -
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PyJNIus
Access Java classes from Python
Pyjnius is a Python library for accessing Java classes. A Python module to access Java classes as Python classes using the Java Native Interface (JNI). Warning: the pypi name is now pyjnius instead of jnius. When you use autoclass, it will discover all the methods and fields of the class and resolve them. You can use the signatures method of JavaMethod and JavaMultipleMethod, to inspect the discovered signatures of a method of an object. -
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LLaMA 3
The official Meta Llama 3 GitHub site
...Even as a deprecated repo, it documents the transition path and preserves references that clarify how Llama 3 releases map into the current ecosystem. Practically, it functioned as a bridge between Llama 2 and later Llama releases by standardizing distribution and starter code for inference and fine-tuning. Teams still treat it as historical reference material for version lineage and migration notes.
