Xing-lil/Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Repositories
Xing-lil/PaddleFleet
Core Functional Library for Distributed Training
Xing-lil/mcore-bridge
MCore-Bridge: Providing Megatron-Core model definitions for state-of-the-art large models and making Megatron training as simple as Transformers — with support for 300+ large language models (Qwen3-Next, GLM-5.2, Deepseek-V4, MiniMax-2.7, ...) and 200+ multimodal large models (Qwen3.5, Qwen3-Omni, Gemma4, ...).
Xing-lil/ms-swift
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.6, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Gemma4, Llava, Phi4, ...) (AAAI 2025).
Xing-lil/Megatron-LM
Ongoing research training transformer models at scale
Xing-lil/PaddleFormers
PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.
Xing-lil/PaddleNLP
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
Xing-lil/PaddleScience
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
Xing-lil/deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
Xing-lil/ERNIE
The official repository for ERNIE 4.5 and ERNIEKit – its industrial-grade development toolkit based on PaddlePaddle.
Xing-lil/docs
Documentations for PaddlePaddle
Xing-lil/PaddleMIX
Paddle Multimodal Integration and eXploration, supporting mainstream multi-modal tasks, including end-to-end large-scale multi-modal pretrain models and diffusion model toolbox. Equipped with high performance and flexibility.
Xing-lil/PaDiff
Paddle Automatically Diff Precision Toolkits.
Xing-lil/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration