Streamlit based implementation for the The Segment Anything Model (SAM) developed by Meta AI research

A small walkthrough of Facebook's TransCoder Pretrained model for Code Conversion

Unofficial PyTorch implementation of the paper - Dynamic Meta-Embeddings for Improved Sentence Representations, EMNLP 2018

tf-keras re-implementation of ConvNeXt (https://arxiv.org/abs/2201.03545) from Facebook Research.

FAIR ESM model conversion to ONNX with extra model argument support

Analyzes marketing copy using behavioral signals and simulated engagement metrics.

METAØNEX is an advanced Facebook Intelligence Suite for security research & OSINT. It enables account discovery via email/phone/username, full profile extraction, social mapping, batch processing with proxy rotation & rate limiting. Built for ethical hacking, penetration testing & privacy awareness education. Use responsibly.

Contextual Thesaurus with Facebook Infersent Embeddings

Chatbot created with Facebook AI Research technology. Built with Flask

PySlowFast, the official video understanding framework from Facebook AI Research (FAIR), to train, evaluate, and reproduce state-of-the-art video models on the UCF24 action detection dataset. It supports customizable training pipelines, model fine-tuning, and evaluation for video-based action recognition and spatio-temporal localization tasks.

Benchmarking energy-efficient optimizations (DepthShrinker, QAT, pruning) on MobileNetV2 using Tiny ImageNet with power-aware evaluation.