Search Results for "recipes"
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Showing 272 open source projects for "recipes"
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Tandoor Recipes
Application for managing recipes, planning meals, building shopping
Application for managing recipes, planning meals, building shopping lists and much much more! This application is meant for people with a collection of recipes they want to share with family and friends or simply store them in a nicely organized way. A basic permission system exists but this application is not meant to be run as a public page. Tandoor is developed by volunteers in their free time just because its fun. -
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Llama Recipes
Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT method
The 'llama-recipes' repository is a companion to the Meta Llama models. We support the latest version, Llama 3.1, in this repository. The goal is to provide a scalable library for fine-tuning Meta Llama models, along with some example scripts and notebooks to quickly get started with using the models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama and other tools in the LLM ecosystem. -
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Go Recipes
Collection of handy tools for Go projects
Visualize the distribution of code coverage in your project. This helps to identify code areas with high and low coverage. Useful when you have a large project with lots of files and packages. This 2D image-hash of your project should be more representative than a single number. For each module, the node representing the greatest version (i.e., the version chosen by Go's minimal version selection algorithm) is colored green. Other nodes, which aren't in the final build list, are colored grey... -
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Kubernetes Network Policy Recipes
Example recipes for Kubernetes Network Policies that you can just copy
...These recipes help secure Kubernetes clusters by ensuring that pods communicate only with allowed peers, reduce attack surfaces, and enforce least-privilege connectivity at the network layer. The recipes scale from simple “deny all traffic by default” policies to more advanced micro-segmentation patterns for multi-tier apps (frontend/backends) and platform-level isolation for CI/CD systems or service meshes. -
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Norish
A realtime, self-hosted recipe app for families & friends
Norish is a realtime, self-hosted recipe and meal-planning app built for families, friends, and collaborative cooks who want to maintain a shared catalogue of recipes and grocery lists. The project emphasizes simplicity and immediacy, syncing changes across multiple clients using WebSockets so that updates to recipes, groceries, or meal plans appear instantly for all users. The app allows users to import recipes from URLs and even fallback to AI parsing when needed, with multimedia support that includes video import from popular platforms when AI is configured. ... -
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What to cook?
Get a recipe to cook today, based on the ingredients you have at home
WhatToCook is a recipe recommendation tool that suggests recipes based on available ingredients, helping users reduce food waste by utilizing what they have on hand. -
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OpenRewrite
Automated mass refactoring of source code
...Patch security vulnerabilities across 100s of repositories at once. OpenRewrite automates code refactoring and remediation tasks for you, enabling developers to deliver more business value. OpenRewrite's refactoring engine and recipes will always be open-source. Build tool plugins like OpenRewrite Gradle Plugin and OpenRewrite Maven Plugin help you run these recipes on one repository at a time. Moderne is a complementary product that executes OpenRewrite recipes at scale on hundreds of millions of lines of code and enables mass-committing of results. Moderne freely runs a public service for the benefit of thousands of open-source projects. -
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what-to-eat
An AI-based intelligent recipe generation platform
what-to-eat is an AI-powered recipe generation platform that helps users decide what to cook by generating customized recipes based on ingredients, cuisine preferences, and dietary considerations. The application combines modern frontend technologies with large language models to create a fully interactive cooking assistant that can produce detailed recipes, nutritional analysis, and even visual representations of dishes. It supports a wide range of cuisines, including traditional Chinese regional styles and international dishes, making it versatile for different cultural preferences. ... -
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LitGPT
20+ high-performance LLMs with recipes to pretrain, finetune at scale
LitGPT is a collection of over 20 high-performance large language models (LLMs) accompanied by recipes to pretrain, finetune, and deploy them at scale. It provides implementations without abstractions, making it beginner-friendly while offering advanced features like flash attention and support for various precision levels. LitGPT is designed to run efficiently across multiple GPUs or TPUs, catering to both small-scale and large-scale deployments. -
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HowToCook
Programmer's guide about how to cook at home
HowToCook is a Chinese-language repository of cooking recipes and tutorials, formatted in Markdown for easy reading and version control. It covers traditional Chinese, Western, and fusion dishes, with step-by-step instructions, ingredient lists, and images where applicable. Ideal for home cooks and learners, it offers a neat, text-based kitchen manual that can be browsed online or printed for reference. -
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Deployer
Deployment tool with support for popular frameworks out of the box
...Deployer is a cli tool for deployment of any PHP applications, including frameworks such as Laravel, Symfony, Zend Framework and many more. Main concept of Deployer is recipe, a php file containing tasks definitions. Recipe can require other recipes and extend/ override functionality. Also Deployer comes with bunch of ready to use recipes from community for Slack, etc. Deployer can be easily installed via composer or as phar archive. By default deployer keeps the last 5 releases, but you can increase this number by modifying the associated parameter. You may want to run some task before/after other tasks. ... -
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SparseML
Libraries for applying sparsification recipes to neural networks
SparseML is an optimization toolkit for training and deploying deep learning models using sparsification techniques like pruning and quantization to improve efficiency. -
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BAT.jl
A Bayesian Analysis Toolkit in Julia
Welcome to BAT, a Bayesian analysis toolkit in Julia. BAT.jl offers a variety of posterior sampling, mode estimation and integration algorithms, supplemented by plotting recipes and I/O functionality. BAT.jl originated as a rewrite/redesign of BAT, the Bayesian Analysis Toolkit in C++. BAT.jl now offer a different set of functionality and a wider variety of algorithms than its C++ predecessor. -
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The Alignment Handbook
Robust recipes to align language models with human and AI preferences
...The project focuses on the post-training stage of model development, where models are refined after pre-training to behave more helpfully, safely, and reliably in real-world applications. It provides detailed training recipes that explain how to perform tasks such as supervised fine-tuning, preference modeling, and reinforcement learning from human feedback. The handbook also includes reproducible workflows for training instruction-following models and evaluating alignment quality across different datasets and benchmarks. One of its goals is to bridge the gap between academic research on alignment methods and practical engineering implementation. -
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Llama Cookbook
Solve end to end problems using Llama model family
The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models -
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ESPnet
End-to-end speech processing toolkit
ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while still benefiting from the robust data preparation practices developed in the speech community. ESPnet provides many ready-to-run recipes for popular academic benchmarks, making it straightforward to reproduce published results or serve as baselines for new research. ... -
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CyberChef
A web app for encryption, encoding, compression and data analysis
CyberChef, developed by GCHQ, is a versatile web application dubbed the "Cyber Swiss Army Knife." It enables users to perform a wide array of operations on data, including encryption, encoding, compression, and analysis, all within a browser interface. -
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Chakra UI
Chakra UI is a component system for building SaaS products with speed
...To use Chakra UI components, all you need to do is install the chakra-ui/react package and its peer dependencies. Works with Next.js RSC. Component system for building SaaS products with speed. Fully customizable with typography, tokens, and component “recipes”. -
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Casey just
Just a command runner
just is a handy way to save and run project-specific commands. -
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AudioCraft
Audiocraft is a library for audio processing and generation
...The repo provides inference scripts, checkpoints, and simple Python APIs so you can generate clips from prompts or incorporate the models into applications. It also contains training code and recipes, so researchers can fine-tune on custom data or explore new objectives without building infrastructure from scratch. Example notebooks, CLI tools, and audio utilities help with prompt design, conditioning on reference audio, and post-processing to produce ready-to-share outputs. -
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Yggdrasil
Collection of builder repositories for BinaryBuilder.jl
This repository contains recipes for building binaries for Julia packages using BinaryBuilder.jl. -
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JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
...This makes learning focus on semantics and structure, yielding features that transfer well with simple linear probes and minimal fine-tuning. The repository provides training recipes, data pipelines, and evaluation utilities for image JEPA variants and often includes ablations that illuminate which masking and architectural choices matter. Because the objective is non-autoregressive and operates in embedding space, JEPA tends to be compute-efficient and stable at scale. The approach has become a strong alternative to contrastive or pixel-reconstruction methods for representation learning. -
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CosyVoice
Multi-lingual large voice generation model, providing inference
...CosyVoice 2.0 significantly improves on version 1.0 by boosting accuracy, stability, speed, and overall speech quality, making it more suitable for production environments. The repository contains training recipes, inference pipelines, deployment scripts, and integration examples, positioning it as a comprehensive toolkit rather than just a set of model weights. -
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RLHF-Reward-Modeling
Recipes to train reward model for RLHF
...In RLHF pipelines, reward models are responsible for evaluating generated responses and assigning scores that guide the model toward outputs that better match human preferences. The repository provides training recipes and implementations for building reward and preference models using modern machine learning frameworks. It supports multiple optimization strategies commonly used in alignment pipelines, including reinforcement learning with PPO, iterative supervised fine-tuning using rejection sampling, and direct preference optimization methods. ... -
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Omnilingual ASR
Omnilingual ASR Open-Source Multilingual SpeechRecognition
Omnilingual-ASR is a research codebase exploring automatic speech recognition that generalizes across a very large number of languages using shared modeling and training recipes. It focuses on leveraging self-supervised audio pretraining and scalable fine-tuning so low-resource languages can benefit from high-resource data. The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new language sets. It emphasizes modularity: acoustic modeling, language modeling, tokenization, and decoding are separable pieces you can swap or ablate. ...
