Found 663 repositories(showing 30)
An open-source C++ library developed and used at Facebook.
bazelment
Make bazel an out of box solution for C++/Java developers
evancharlton
Flickr Volley demo
mrDIMAS
No description available
edufolly
Basic form fields and utilities. Maybe a humble Flutter project boilerplate.
user1342
Open-source LLM Prompt-Injection and Jailbreaking Playground
miyanokomiya
No description available
storypku
rules_folly: Bazel Build Rules for Folly
dfrib
https://dfrib.github.io/a-foliage-of-folly/
QunxingHu
An lite version of facebook folly, contains fbvector and fbstring only.
Templar66
No description available
DenisovNikita
Position-based conference call system
gleke
基于folly、wangle和proxygen的c++11基础库
Roadcrosser
Applying the stupidity of bogosort to file transfers is the height of folly.
dillonhuff
First order logic in Haskell
tattlemuss
Visual display and analysis of Tim Follin's Atari ST sound routine.
folly-org
A text editor made with Zig and Luau.
concord
zookeeper c++11. Uses facebook folly.
tian-yuan
基于 facebook 的 folly 和 wangle 开发的 c++ 分布式服务基础框架
r10a
Standalone Eventcounts module from facebook/folly
ParametricPress
Source code for Flatland Follies: An Adjunct Simulator
baskeboler
REST data server implemented with proxygen and rocksdb
bincrafters
[OBSOLETE] The recipe is now in https://github.com/conan-io/conan-center-index
Yeolar
A C++11 foundation and network library.
robertxa
Base de données topographiques du massif du Folly (Samoëns, France)
BolajiOlajide
keep track of reactions to a message
kremius
C++ board engine based on Proxygen
iShafayet
Khilji's Folly - A historic hill defense game for js13k 2023
GKantidakis
This repository stores the R-code of a research project that compared statistical models (SM) with machine learning (ML) techniques for competing risks in private extremity soft-tissue sarcoma (eSTS) data, and a comprehensive example in publicly available R data for Follicular Cell Lymphoma (data "follic"). The aim was to develop and validate prognostic clinical prediction models for competing risks (CRs) with small/medium sample size and in a low-dimensional setting. Two SM (cause-specific Cox, Fine-Gray) and three ML techniques (PLANNCR original, PLANNCR extended, RSFCR) were compared in terms of discrimination and calibration. -Notes- PLANNCR, Partial Logistic Artificial Neural Network for Competing Risks; RSFCR, Random Survival Forests for Competing Risks.
tnie
future in folly