Technical principles related to large models
The largest collection of PyTorch image encoders / backbones
Advanced evolutionary computation library built on top of PyTorch
An API standard for single-agent reinforcement learning environments
Implementation of RLHF (Reinforcement Learning with Human Feedback)
Massively parallel rigidbody physics simulation
The easiest, and fastest way to run AI-generated Python code safely
An Easy-to-use, Scalable and High-performance RLHF Framework
A guidance language for controlling large language models
General proxy performance testing tool based on Clash using Telegram
A Telegram RSS bot that cares about your reading experience
Standalone, small, language-neutral
Reference implementations of MLPerf™ training benchmarks
A Python package to assess and improve fairness of ML models
TFX is an end-to-end platform for deploying production ML pipelines
TimeGPT-1: production ready pre-trained Time Series Foundation Model
Pretrained (Language) Models for Probabilistic Time Series Forecasting
Explainability and Interpretability to Develop Reliable ML models
A high performance implementation of HDBSCAN clustering
Python framework for adversarial attacks, and data augmentation
Hummingbird compiles trained ML models into tensor computation
SkyPilot: Run AI and batch jobs on any infra
Bibtex parser for Python 3
Sample cloud-first application with 10 microservices
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle