Search Results for "source code" - Page 11
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Showing 507 open source projects for "source code"
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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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scikit-image
Image processing in Python
scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image builds on scipy.ndimage to provide a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! Read about our mission, vision, and values and how we govern the project. Major proposals... -
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MoCo (Momentum Contrast)
Self-supervised visual learning using momentum contrast in PyTorch
MoCo is an open source PyTorch implementation developed by Facebook AI Research (FAIR) for the papers “Momentum Contrast for Unsupervised Visual Representation Learning” (He et al., 2019) and “Improved Baselines with Momentum Contrastive Learning” (Chen et al., 2020). It introduces Momentum Contrast (MoCo), a scalable approach to self-supervised learning that enables visual representation learning without labeled data. The core idea of MoCo is to maintain a dynamic dictionary with a... -
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Step1X-Edit
A SOTA open-source image editing model
Step1X-Edit is a state-of-the-art open-source image editing model/framework that uses a multimodal large language model (LLM) together with a diffusion-based image decoder to let users edit images simply via natural-language instructions plus a reference image. You supply an existing image and a textual command — e.g. “add a ruby pendant on the girl’s neck” or “make the background a sunset over mountains” — and the model interprets the instruction, computes a latent embedding combining the... -
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Surya
Implementation of the Surya Foundation Model for Heliophysics
Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture,... -
Lightspeed golf course management softwareFrom tee sheet management, point of sale and payment processing to marketing, automation, reporting and more—Lightspeed is built for the pro shop, restaurant, back office, beverage cart and beyond.
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Swirl
Swirl queries any number of data sources with APIs
Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank... -
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Lingvo
Framework for building neural networks
Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state... -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and... -
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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and... -
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Prompt Engineering Interactive Tutorial
Anthropic's Interactive Prompt Engineering Tutorial
Prompt-eng-interactive-tutorial is a comprehensive, hands-on tutorial that teaches the craft of prompt engineering with Claude through guided, executable lessons. It starts with the anatomy of a good prompt and moves into techniques that deliver the “80/20” gains—separating instructions from data, specifying schemas, and setting evaluation criteria. The course leans heavily on realistic failure modes (ambiguity, hallucination, brittle instructions) and shows how to iteratively debug prompts... -
eProcurement SoftwareeBuyerAssist by Eyvo is a cloud-based procurement solution designed for businesses of all sizes and industries. Fully modular and scalable, it streamlines the entire procurement lifecycle—from requisition to fulfillment. The platform includes powerful tools for strategic sourcing, supplier management, warehouse operations, and contract oversight. Additional modules cover purchase orders, approval workflows, inventory and asset management, customer orders, budget control, cost accounting, invoice matching, vendor credit checks, and risk analysis. eBuyerAssist centralizes all procurement functions into a single, easy-to-use system—improving visibility, control, and efficiency across your organization. Whether you're aiming to reduce costs, enhance compliance, or align procurement with broader business goals, eBuyerAssist helps you get there faster, smarter, and with measurable results.
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Instructor
Structured outputs for llms
Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of... -
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Kubeflow pipelines
Machine Learning Pipelines for Kubeflow
Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. A pipeline is a description of an ML workflow, including all of the components in the workflow and how they combine in the form of a graph. The pipeline includes the definition of the inputs (parameters) required to run the pipeline and the inputs and outputs of each component. A pipeline component is a self-contained set of user code, packaged as... -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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DreamO
A Unified Framework for Image Customization
DreamO is a unified, open-source framework from ByteDance for advanced image customization and generation that consolidates multiple “image manipulation” tasks into a single system, rather than requiring separate specialized models. Built on a diffusion-transformer (DiT) backbone, it supports a diverse set of tasks — including identity preservation, virtual “try-on” (e.g. clothing, accessories), style transfer, IP adaptation (objects/characters), and layout/condition-aware customizations —... -
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Dia
A TTS model capable of generating ultra-realistic dialogue
Dia is a neural text-to-speech model designed specifically for generating ultra-realistic dialogue in a single pass. Instead of focusing on isolated sentences or flat narration, it is optimized for conversational audio, complete with natural turn-taking, prosody, and pacing. The model can be conditioned on a reference audio sample, allowing you to control emotion, tone, and other stylistic aspects of the speech. It can also produce nonverbal vocalizations like laughter, coughs, clearing the... -
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verl
Volcano Engine Reinforcement Learning for LLMs
VERL is a reinforcement-learning–oriented toolkit designed to train and align modern AI systems, from language models to decision-making agents. It brings together supervised fine-tuning, preference modeling, and online RL into one coherent training stack so teams can move from raw data to aligned policies with minimal glue code. The library focuses on scalability and efficiency, offering distributed training loops, mixed precision, and replay/buffering utilities that keep accelerators busy.... -
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Mesh R-CNN
code for Mesh R-CNN, ICCV 2019
Mesh R-CNN is a 3D reconstruction and object understanding framework developed by Facebook Research that extends Mask R-CNN into the 3D domain. Built on top of Detectron2 and PyTorch3D, Mesh R-CNN enables end-to-end 3D mesh prediction directly from single RGB images. The model learns to detect, segment, and reconstruct detailed 3D mesh representations of objects in natural images, bridging the gap between 2D perception and 3D understanding. Unlike voxel-based or point-based approaches, Mesh... -
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SAM 2
The repository provides code for running inference with SAM 2
SAM2 is a next-generation version of the Segment Anything Model (SAM), designed to improve performance, generalization, and efficiency in promptable image segmentation tasks. It retains the core promptable interface—accepting points, boxes, or masks—but incorporates architectural and training enhancements to produce higher-fidelity masks, better boundary adherence, and robustness to complex scenes. The updated model is optimized for faster inference and lower memory use, enabling real-time... -
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ChatGPT Retrieval Plugin
The ChatGPT Retrieval Plugin lets you easily find personal documents
The chatgpt-retrieval-plugin repository implements a semantic retrieval backend that lets ChatGPT (or GPT-powered tools) access private or organizational documents in natural language by combining vector search, embedding models, and plugin infrastructure. It can serve as a custom GPT plugin or function-calling backend so that a chat session can “look up” relevant documents based on user queries, inject those results into context, and respond more knowledgeably about a private knowledge... -
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NeuralProphet
A simple forecasting package
NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in... -
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Thinc
A refreshing functional take on deep learning
Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose,... -
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AutoGluon
AutoGluon: AutoML for Image, Text, and Tabular Data
AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on automated stack ensembling, deep learning, and real-world applications spanning image, text, and tabular data. Intended for both ML beginners and experts, AutoGluon enables you to quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code. Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge. Leverage automatic hyperparameter tuning,... -
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Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several... -
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1D Visual Tokenization and Generation
This repo contains the code for 1D tokenizer and generator
The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. This compact... -
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UNO
A Universal Customization Method for Single and Multi Conditioning
UNO is a project by ByteDance introduced in 2025, titled “A Universal Customization Method for Both Single and Multi-Subject Conditioning.” It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. Because the project is... -
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Sa2VA
Official Repo For "Sa2VA: Marrying SAM2 with LLaVA
Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about...
