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- GPU Cluster Monitoring (GCM): Large-Scale AI Research Cluster Monitoring
- FAIR Sequence Modeling Toolkit 2
- PrivacyGuard platform for Privacy Attacks and Analysis. Perform privacy analyses of ML models using Inference Attacks and Extraction Attacks. PrivacyGuard library implements varied, SotA privacy attacks, along with tooling to analyze results. Please see the README and tutorials to get started!
- A library for preparing data for machine translation research (monolingual preprocessing, bitext mining, etc.) built by the FAIR NLLB team.
- An open source library designed to provide community examples of Joint Embedding Predictive Architectures (JEPAs). It contains code and examples for learning representations from images, video, and action-conditioned video, as well as planning using JEPA-based models.
- This repository contains the training code from paper "SpidR Learning Fast and Stable Linguistic Units for Spoken Language Models Without Supervision". SpidR is a self-supervised speech representation model that efficiently learns strong representations for spoken language modeling.
- This repository provides a comprehensive benchmark for evaluating the performance of neural watermarking techniques. The benchmark includes a variety of datasets, evaluation metrics, and tools for training and testing neural networks for watermarking.
- A dynamic binary instrumentation tool for tracing and analyzing CUDA kernel instructions.
- Open source impl of **MV-DUSt3R+ Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds** from Meta Reality Labs. Project page https://mv-dust3rp.github.io/
- Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reprodu…