Search Results for "reference" - Page 5
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Showing 185 open source projects for "reference"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Lightning-Hydra-Template
PyTorch Lightning + Hydra. A very user-friendly template
Convenient all-in-one technology stack for deep learning prototyping - allows you to rapidly iterate over new models, datasets and tasks on different hardware accelerators like CPUs, multi-GPUs or TPUs. A collection of best practices for efficient workflow and reproducibility. Thoroughly commented - you can use this repo as a reference and educational resource. Not fitted for data engineering - the template configuration setup is not designed for building data processing pipelines that depend on each other. PyTorch Lightning, a lightweight PyTorch wrapper for high-performance AI research. Think of it as a framework for organizing your PyTorch code. Hydra, a framework for elegantly configuring complex applications. ... -
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FastViT
This repository contains the official implementation of research
...Training and inference recipes highlight straightforward integration into common vision tasks such as classification, detection, and segmentation. The codebase provides reference implementations and checkpoints that make it easy to evaluate or fine-tune on downstream datasets. In practice, FastViT offers drop-in backbones that reduce compute and memory pressure without exotic training tricks. -
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LLaMA
Inference code for Llama models
“Llama” is the repository from Meta (formerly Facebook/Meta Research) containing the inference code for LLaMA (Large Language Model Meta AI) models. It provides utilities to load pre-trained LLaMA model weights, run inference (text generation, chat, completions), and work with tokenizers. Tokenizer utilities, download scripts, shell helpers to fetch model weights with correct licensing/permissions. Includes example scripts for chat completions and text completions to show how to call the... -
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hloc
Visual localization made easy with hloc
...This codebase won the indoor/outdoor localization challenges at CVPR 2020 and ECCV 2020, in combination with SuperGlue, our graph neural network for feature matching. We provide step-by-step guides to localize with Aachen, InLoc, and to generate reference poses for your own data using SfM. Just download the datasets and you're reading to go! The notebook pipeline_InLoc.ipynb shows the steps for localizing with InLoc. It's much simpler since a 3D SfM model is not needed. We show in pipeline_SfM.ipynb how to run 3D reconstruction for an unordered set of images. This generates reference poses, and a nice sparse 3D model suitable for localization with the same pipeline as Aachen. -
Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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Edge GPT
Reverse engineered API of Microsoft's Bing Chat
...As with many reverse-engineered clients, it depended on upstream behavior that could change, and the project’s lifecycle reflected that reality. The repository was later archived, meaning it is read-only and no longer actively maintained, but it remains a reference point for how developers approached unofficial access to Bing Chat. In essence, EdgeGPT served as a bridge between an interactive chat -
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Metaseq
Repo for external large-scale work
...Built on top of PyTorch, it provides distributed training, model sharding, mixed-precision computation, and memory-efficient checkpointing to support models with hundreds of billions of parameters. The framework was used internally at Meta to train models like OPT (Open Pre-trained Transformer) and serves as a reference implementation for scaling transformer architectures efficiently across GPUs and nodes. It supports both pretraining and fine-tuning workflows with data pipelines for text, multilingual corpora, and custom tokenization schemes. Metaseq also includes APIs for evaluation, generation, and model serving, enabling seamless transitions from training to inference. -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
...The repository provides an open-source PyTorch framework with data loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. The project also releases several fully anonymized public MRI datasets, including knee, brain, and prostate scans. -
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OpenAI OpenAPI
OpenAPI specification for the OpenAI API
...The repository ensures that developers and toolchains can integrate with OpenAI services using a consistent schema across SDKs, code generators, and API clients. It contains both an automatically documented version of the spec and a manually updated branch for reference. Developers can use this specification to generate client libraries, validate requests and responses, or explore the API structure in compatible tools. The project is actively maintained with tagged releases, issues, and contributions from multiple collaborators. Its goal is to improve transparency, developer experience, and interoperability when building applications powered by OpenAI’s models. -
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ChatGPT Plugins Collection
An unofficial collection of Plugins for ChatGPT
...The collection provides a variety of plugin implementations that showcase different use cases, helping developers learn how to extend ChatGPT’s functionality. It is designed to serve both as a learning resource for beginners and a reference point for more experienced developers. By centralizing community contributions, the repository highlights practical applications of plugins across domains such as productivity, data access, and automation. The project also serves as a starting point for developers interested in building their own custom plugins, offering inspiration and code samples. ... -
All-in-one security tool helps you prevent ransomware and breaches.Blumira’s detection and response platform enables faster resolution of threats to help you stop ransomware attacks and prevent data breaches. We surface real threats, providing meaningful findings so you know what to prioritize. With our 3-step rapid response, you can automatically block known threats, use our playbooks for easy remediation, or contact our security team for additional guidance. Our responsive security team helps with onboarding, triage and ongoing consultations to continuously help your organization improve your security coverage.
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LM Human Preferences
Code for the paper Fine-Tuning Language Models from Human Preferences
lm-human-preferences is the official OpenAI codebase that implements the method from the paper Fine-Tuning Language Models from Human Preferences. Its purpose is to show how to align language models with human judgments by training a reward model from human comparisons and then fine-tuning a policy model using that reward signal. The repository includes scripts to train the reward model (learning to rank or score pairs of outputs), and to fine-tune a policy (a language model) with... -
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handson-ml2
Jupyter notebooks that walk you through the fundamentals of ML
...The material favors clear explanations and runnable code over theory alone, so learners can iterate, visualize, and debug as they go. It’s suitable for self-study, classrooms, and as a reference for practitioners who want concise, working examples of common ML tasks. -
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NÜWA - Pytorch
Implementation of NÜWA, attention network for text to video synthesis
...You can easily do this as well, given you train a VQGanVAE on the sketches beforehand. Then, you will use NUWASketch instead of NUWA, which can accept the sketch VAE as a reference. This repository will also offer a variant of NUWA that can produce both video and audio. For now, the audio will need to be encoded manually. -
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AllenNLP
An open-source NLP research library, built on PyTorch
AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional allennlp subcommands. There is ecosystem of open source plugins, some of which are maintained by the AllenNLP team here at AI2, and some of which are maintained by the broader community. ... -
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handson-ml
Teaching you the fundamentals of Machine Learning in python
handson-ml hosts the notebooks for the first edition of the same hands-on ML book, reflecting the tooling and idioms of its time while teaching durable concepts. It walks through supervised and unsupervised learning with scikit-learn, then introduces deep learning using the earlier TensorFlow 1 graph-execution style. The examples underscore fundamentals like bias-variance trade-offs, regularization, and proper validation, grounding learners before they move to deep nets. Even though the deep... -
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Apple Neural Engine (ANE) Transformers
Reference implementation of the Transformer architecture optimized
ANE Transformers is a reference PyTorch implementation of Transformer components optimized for Apple Neural Engine on devices with A14 or newer and on Macs with M1 or newer chips. It demonstrates how to structure attention and related layers to achieve substantial speedups and lower peak memory compared to baseline implementations when deployed to ANE. The repository targets practitioners who want to keep familiar PyTorch modeling while preparing models for Core ML/ANE execution paths. ... -
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DomE
Implements a reference architecture for creating information systems
DomE Experiment is an implementation of a reference architecture for creating information systems from the automated evolution of the domain model. The architecture comprises elements that guarantee user access through automatically generated interfaces for various devices, integration with external information sources, data and operations security, automatic generation of analytical information, and automatic control of business processes. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. ... -
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Deeplearning.ai
Study notes, summaries, and auxiliary materials for deep learning
...The explanations aim to bridge theory and practice, often connecting mathematical intuition to code-level implications. By organizing the content as “books” or structured notes, it gives students a consistent reference to revisit as models and tooling evolve. Many learners use it to supplement course videos, reinforcing concepts before implementing assignments or projects. As a consolidated guide, it reduces context-switching and helps build a durable mental model of deep learning fundamentals. -
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Following Instructions with Feedback
Training Language Models to Follow Instructions with Human Feedback
...The repo hosts the model card, sample automatic evaluation outputs, and labeling guidelines used in the process. It is explicitly tied to the “Training language models to follow instructions with human feedback” paper, and serves as a reference for how OpenAI collects annotation guidelines, runs preference comparisons, and evaluates model behaviors. The repository is not a full implementation of the entire RLHF pipeline, but rather an archival hub supporting the published research—providing transparency around evaluation and human labeling standards. It includes directories such as automatic-eval-samples (samples of model outputs on benchmark tasks) and a model-card.md that describes the InstructGPT models’ intended behavior, limitations, and biases. -
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Mycroft
Mycroft Core, the Mycroft Artificial Intelligence platform
Mycroft is the world’s leading open source voice assistant. It is private by default and completely customizable. Our software runs on many platforms, on desktop, our reference hardware, a Raspberry Pi, or your own custom hardware. Our open-source, modular system can be ported to your device or environment, at any price point. Whether you make voice-assistants, televisions, or microwaves. Whether you have a 5-room BnB or a 1000-room hotel. Your customers will get access to all the necessities of a voice assistant. ... -
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Mocking Bird
Clone a voice in 5 seconds to generate arbitrary speech in real-time
MockingBird is an open-source voice cloning and real-time speech generation toolkit that lets you clone a speaker’s voice from a short audio sample (reportedly as little as 5 seconds) and then synthesize arbitrary speech in that voice. It builds on deep-learning based TTS / voice-cloning technology (in the lineage of projects such as Real-Time-Voice-Cloning), but extends it with support for Mandarin Chinese and multiple Chinese speech datasets — broadening its applicability beyond English.... -
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Parakeet
PAddle PARAllel text-to-speech toolKIT
...It is built on PaddlePaddle dynamic graph and includes many influential TTS models. In order to facilitate exploiting the existing TTS models directly and developing the new ones, Parakeet selects typical models and provides their reference implementations in PaddlePaddle. Further more, Parakeet abstracts the TTS pipeline and standardizes the procedure of data preprocessing, common module sharing, model configuration, and the process of training and synthesis. The models supported here include Text FrontEnd, end-to-end Acoustic models and Vocoders. -
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fairseq-lua
Facebook AI Research Sequence-to-Sequence Toolkit
...Although now deprecated in favor of the PyTorch rewrite, fairseq-lua played a key role in advancing large-scale NMT systems, such as early versions of Facebook’s production translation models. It remains an important historical reference for neural sequence learning frameworks. -
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MTBook
Machine Translation: Foundations and Models
...Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. This book is written in tex, and all source codes are open. This book is divided into four parts, each of which consists of several chapters. The order of the chapters refers to the time context of the development of machine translation technology, while taking into account the internal logic of the machine translation knowledge system. -
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CleverHans
An adversarial example library for constructing attacks
...In versions v3.1.0 and prior, CleverHans supported TF1; the code for v3.1.0 can be found under cleverhans_v3.1.0/ or by checking out a prior Github release. The library focuses on providing a reference implementation of attacks against machine learning models to help with benchmarking models against adversarial examples.
