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Showing 14 open source projects for "cover"
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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django-webpack-loader
Transparently use webpack with django
Use webpack to generate your static bundles without django's static files or opaque wrappers. Django webpack loader consumes the output generated by webpack-bundle-tracker and lets you use the generated bundles in Django. Test cases cover Django>=2.0 on Python>=3.5. 100% code coverage is the target so we can be sure everything works anytime. It should probably work on older versions of Django as well but the package does not ship any test cases for them. Before configuring django-webpack-loader, let's first configure what's necessary on the webpack-bundle-tracker side. ... -
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Promgen
Promgen is a configuration file generator for Prometheus
Promgen is a configuration file generator for Prometheus. Promgen is a web application written with Django and can help you do several jobs. The primary management UI is a Django application and many of the concepts that apply to a typical Django application will apply to Promgen. Configure Prometheus to load the target file from Prometheus and configure AlertManager to send notifications back to Promgen. Arbitrary Django settings can be set for the Promgen web app by adding those under the... -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
...Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. Each baseline emphasizes reproducibility: fixed seeds, standard splits, and strong metrics such as calibration error, AUROC for OOD, and accuracy under shift. -
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Think Bayes 2
Text and code for the second edition of Think Bayes, by Allen Downey
...Each chapter is presented as a Jupyter notebook where readers can study the text, run examples, and complete exercises. Separate solution materials help learners check their work and explore alternative approaches. The lessons cover probability distributions, Bayesian updating, estimation, prediction, comparison, and decision-making. Notebooks can run in Google Colab or be downloaded for local use. The repository also contains book sources, supporting code, and environment files for reproducible study. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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My Python Eggs
Python Examples
...Rather than being a single cohesive application, it functions as a repository of utilities that demonstrate how Python can be used to solve everyday problems and automate repetitive tasks. The scripts cover a wide range of topics, including file management, networking, system monitoring, web scraping, and even simple games, making it a versatile learning resource. Many of the programs are designed to reduce manual workload by automating tasks such as renaming files, scanning directories, or checking system information. The repository also includes examples of more advanced concepts like multithreading, API interaction, and GUI development, providing a gradual learning curve for beginners. -
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ComfyUI IPAdapter plus
ComfyUI reference implementation for IPAdapter models
...The project treats IPAdapter like a one-image LoRA, making it useful when users want visual influence without full model training. It includes example workflows that cover the main IPAdapter functions and help users build practical ComfyUI graphs. The extension supports unified loaders, model loaders, advanced apply nodes, attention masks, reference image weighting, and different embedding strategies. It is now in maintenance-only mode, so it is best used by ComfyUI users who need established IPAdapter workflows rather than a rapidly evolving plugin. -
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Computer Science Flash Cards
Mini website for testing both general CS knowledge and enforce coding
This repository collects concise flash cards that cover the core ideas of a traditional computer science curriculum with a focus on interview readiness. The cards distill topics like time and space complexity, classic data structures, algorithmic paradigms, operating systems, networking, and databases into short, testable prompts. They are designed for spaced-repetition style study so you can cycle frequently through fundamentals until recall feels automatic. -
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Mythril
Security analysis tool for EVM bytecode. Supports smart contracts
...It's also used (in combination with other tools and techniques) in the MythX security analysis platform. If you are a smart contract developer, we recommend using MythX tools which are optimized for usability and cover a wider range of security issues. The SWC Registry is a community catalog of known smart contract vulnerabilities with detailed descriptions, code samples, and remediations. MythX uses the SWC Registry as its database when scanning smart contracts for security issues. -
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Flask-SQLAlchemy
Adds SQLAlchemy support to Flask
...Flask-SQLAlchemy does not change how SQLAlchemy works or is used. See the SQLAlchemy documentation to learn how to work with the ORM in depth. The documentation here will only cover setting up the extension, not how to use SQLAlchemy. -
Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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Workalendar
Worldwide holidays and workdays computational toolkit
...Workalendar is a Python module that offers classes able to handle calendars, list legal/religious holidays and give working-day-related computation functions. This library is ready for production, although we may warn eventual users: some calendars may not be up-to-date, and this library doesn’t cover all the existing countries on earth (yet). -
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
...You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the theory of transfer learning and show how to apply it in useful projects. The development is on progress! The API will be updated soon, the more talented and light-weight API will be available in this repo! Detailed API documentation and sample jupyter notebooks that explain basic usages of API will be added! -
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pytorch-examples
Simple examples to introduce PyTorch
...It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners and experienced practitioners. By emphasizing readable code, the repository helps users understand how PyTorch’s imperative programming style enables flexible model development. It also serves as a quick reference for common patterns and techniques used in deep learning workflows. ... -
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Tikal's open source Application Development & Deployment is comprised of fully integrated suites that cover the entire software life-cycle, include tools for development and deployment of applications, software configuration management and ASQA.
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Cover Your Asp, a Python coverage analysis tool. This coverage tool correctly traces multithreaded applications and uses deep understanding of Python syntax to provide intelligent reports.
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