Showing 75 open source projects for "facebook"

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  • 1
    granary

    granary

    The social web translator

    The social web translator. Fetches and converts data between social networks, HTML and JSON with microformats2, ActivityStreams/ActivityPub, Atom, JSON Feed, and more. Granary is a library and REST API that fetches and converts between a wide variety of social data sources and formats. Free yourself from silo API chaff and expose the sweet social data foodstuff inside in standard formats and protocols.
    Downloads: 0 This Week
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  • 2
    YAPF

    YAPF

    A formatter for Python files

    ...You can run it as a command-line tool or call it as a library via FormatCode / FormatFile, making it easy to embed in editors, CI, and custom tooling. Styles are highly configurable: start from presets like pep8, google, yapf, or facebook, then override dozens of options in .style.yapf, setup.cfg, or pyproject.toml. It supports recursive directory formatting, line-range formatting, and diff-only output so you can check or fix just the lines you touched.
    Downloads: 1 This Week
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  • 3
    Rasa

    Rasa

    Open source machine learning framework to automate text conversations

    Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual assistants on Facebook Messenger, Slack, Google Hangouts, Webex Teams, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram, and Twilio or on your own custom conversational channels. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forths. In order for a human to have a meaningful exchange with a contextual assistant, the assistant needs to be able to use context to build on things that were previously discussed. ...
    Downloads: 2 This Week
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  • 4
    VGGT-Ω

    VGGT-Ω

    [CVPR 2026 Oral] VGGT Omega

    VGGT-Omega is a Facebook Research computer vision project for feed-forward camera and depth reconstruction. It takes images as input and predicts camera parameters, depth maps, confidence values, and related scene tokens. The project is associated with 3D understanding workflows where models infer scene geometry without a traditional multi-stage reconstruction pipeline.
    Downloads: 9 This Week
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  • 5
    Graphene

    Graphene

    GraphQL in Python Made Easy

    ...Instead of writing GraphQL Schema Definition Langauge (SDL), Python code is written to describe the data provided by your server. Graphene helps you use GraphQL effortlessly in Python, but what is GraphQL? GraphQL is a data query language developed internally by Facebook as an alternative to REST and ad-hoc webservice architectures. With Graphene you have all the tools you need to implement a GraphQL API in Python, with multiple integrations with different frameworks including Django, SQLAlchemy and Google App Engine.
    Downloads: 0 This Week
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  • 6
    Prophet

    Prophet

    Tool for producing high quality forecasts for time series data

    ...It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal setting. We’ve found it to perform better than any other approach in the majority of cases. We fit models in Stan so that you get forecasts in just a few seconds. Get a reasonable forecast on messy data with no manual effort. Prophet is robust to outliers, missing data, and dramatic changes in your time series.
    Downloads: 8 This Week
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  • 7
    MobileLLM

    MobileLLM

    MobileLLM Optimizing Sub-billion Parameter Language Models

    MobileLLM is a lightweight large language model (LLM) framework developed by Facebook Research, optimized for on-device deployment where computational and memory efficiency are critical. Introduced in the ICML 2024 paper “MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases”, it focuses on delivering strong reasoning and generalization capabilities in models under one billion parameters.
    Downloads: 3 This Week
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  • 8
    DjangoBlog

    DjangoBlog

    A blog system based on python3.8 and Django3.0

    ...Complete comment feature, include posting reply comment and email notification. Markdown supporting. Sidebar feature, new articles, most readings, tags, etc. OAuth Login supported, including Google, GitHub, Facebook, Weibo, QQ. Memcache supported, with cache auto refresh. Simple SEO Features, notify Google and Baidu when there was a new article or other things. Simple picture bed feature integrated. django-compressor integrated, auto-compressed css, js. Website exception email notification. When there is an unhandle exception, system will send an email notification. ...
    Downloads: 1 This Week
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  • 9
    Synapse

    Synapse

    Matrix reference homeserver

    ...Eventually-consistent cryptographically secure synchronization of room state across a global open network of federated servers and services. Send and receive extensible messages in a room with (optional) end-to-end encryption. Use 3rd Party IDs (3PIDs) such as email addresses, phone numbers, Facebook accounts to authenticate, identify and discover users on Matrix.
    Downloads: 2 This Week
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  • 10
    DomainBed

    DomainBed

    DomainBed is a suite to test domain generalization algorithms

    DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and Invariant Risk Minimization (IRM) to more advanced techniques like Domain Adversarial Neural Networks (DANN), Adaptive Risk Minimization (ARM), and Invariance Principle Meets Information Bottleneck (IB-ERM/IB-IRM). ...
    Downloads: 1 This Week
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  • 11
    Watermark Anything

    Watermark Anything

    Official implementation of Watermark Anything with Localized Messages

    Watermark Anything (WAM) is an advanced deep learning framework for embedding and detecting localized watermarks in digital images. Developed by Facebook Research, it provides a robust, flexible system that allows users to insert one or multiple watermarks within selected image regions while maintaining visual quality and recoverability. Unlike traditional watermarking methods that rely on uniform embedding, WAM supports spatially localized watermarks, enabling targeted protection of specific image regions or objects. ...
    Downloads: 0 This Week
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  • 12
    Perception Models

    Perception Models

    State-of-the-art Image & Video CLIP, Multimodal Large Language Models

    Perception Models is a state-of-the-art framework developed by Facebook Research for advanced image and video perception tasks. It introduces two primary components: the Perception Encoder (PE) for visual feature extraction and the Perception Language Model (PLM) for multimodal decoding and reasoning. The PE module is a family of vision encoders designed to excel in image and video understanding, surpassing models like SigLIP2, InternVideo2, and DINOv2 across multiple benchmarks. ...
    Downloads: 1 This Week
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  • 13
    fvcore

    fvcore

    Collection of common code shared among different research projects

    fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. ...
    Downloads: 1 This Week
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  • 14
    IPRanges

    IPRanges

    Daily updated lists of cloud, bot, and service IP ranges

    ...It includes address ranges from providers such as Google Cloud, Amazon AWS, Microsoft, Oracle Cloud, and DigitalOcean, as well as well known service platforms like GitHub, Facebook, Twitter, and Telegram. It also tracks IP ranges used by search engine bots and automated agents including Googlebot, Bingbot, and OpenAI’s GPTBot. Lists are published in both IPv4 and IPv6 formats and are regularly updated through automated processes to keep the data current. In addition to provider specific lists, the project also offers merged and combined datasets that aggregate ranges from multiple sources into a single file.
    Downloads: 0 This Week
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  • 15
    MoCo (Momentum Contrast)

    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.
    Downloads: 0 This Week
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  • 16
    Mezzanine

    Mezzanine

    CMS framework for Django

    Mezzanine is a powerful open source content management platform built using the Django framework. In many ways it is like many other content management tools, offering an intuitive interface for managing all of your content. But Mezzanine is different in that it provides most of its functionality by default. While other platforms rely heavily on modules or reusable applications, Mezzanine comes ready with all the functionality you need, making it the more efficient choice. Mezzanine has a...
    Downloads: 2 This Week
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  • 17
    Mesh R-CNN

    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.
    Downloads: 0 This Week
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  • 18
    Diplomacy Cicero

    Diplomacy Cicero

    Code for Cicero, an AI agent that plays the game of Diplomacy

    The project is the codebase for an AI agent named Cicero developed by Facebook Research. It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. ...
    Downloads: 0 This Week
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  • 19
    CO3D (Common Objects in 3D)

    CO3D (Common Objects in 3D)

    Tooling for the Common Objects In 3D dataset

    CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction.
    Downloads: 0 This Week
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  • 20
    Auto Post Facebook Group Simple

    Auto Post Facebook Group Simple

    Tự động đăng bài lên Facebook, hỗ trợ nội dung AI

    Tự động đăng bài lên Facebook với nội dung tạo tự động bằng AI, hỗ trợ chuyển đổi tài khoản facebook phụ và hỗ trợ tải lên hình ảnh.
    Downloads: 3 This Week
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  • 21
    Shumai

    Shumai

    Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun

    Shumai is an experimental differentiable tensor library for TypeScript and JavaScript, developed by Facebook Research. It provides a high-performance framework for numerical computing and machine learning within modern JavaScript runtimes. Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers.
    Downloads: 2 This Week
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  • 22
    autofbpost

    autofbpost

    Semi automate Facebook publishing posts task to groups

    Semi automate Facebook publishing posts task to groups 📦Requirements - Windows or Linux operating system - Chromium based browser (Google Chrome, Microsoft Edge, Brave, Opera) - Stable Internet connection 🚀Installation Simply download the executable No additional installation or dependencies are required. Just download and run the executable file 🎮Usage - Windows: Double-click the `.exe` file or run it from the command line - Linux: Make it executable (`chmod +x autofbpost`) and run it (`....
    Downloads: 3 This Week
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  • 23
    UMD

    UMD

    Universal Multimedia Downloader, URL To Video/Audio. (UMD)

    ⚠️ PROJECT DEPRECATED ⚠️ Universal Media Downloader (UMD) is no longer maintained. This project has been officially replaced by MediaCrate, a better, actively maintained successor with improved performance, stability, and features. ➡ Download MediaCrate here: https://sourceforge.net/projects/mediacrate
    Downloads: 94 This Week
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  • 24
    Grabbit

    Grabbit

    Free Windows app to download videos from YouTube, TikTok, Instagram an

    Grabbit is a desktop video downloader for Windows. Download videos and audio from YouTube, TikTok, Instagram, Facebook, Twitter and more — up to 4K/8K quality. Includes a Chrome Extension to grab videos directly from your browser. No cloud, no account needed. Free tier available. Pro plan from $8.99/month.
    Downloads: 8 This Week
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  • 25
    NeuralProphet

    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 doubt. We are working on an improved documentation. ...
    Downloads: 0 This Week
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