Oneflow-Inc/libai
LiBai(李白): A Toolbox for Large-Scale Distributed Parallel Training
LiBai helps machine learning engineers and researchers efficiently train very large AI models, particularly in natural language processing and computer vision. It takes raw datasets (like images or text) and a chosen model architecture, then outputs a fully trained, high-performing model ready for deployment or further research. This tool is for those working with cutting-edge, data-intensive AI projects who need to optimize training on distributed systems.
406 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher struggling with the complexity and resource demands of training large-scale AI models across multiple GPUs or machines.
Not ideal if you are working with smaller AI models that can be trained efficiently on a single machine, or if you prefer a simpler, less customizable framework for standard tasks.
Stars
406
Forks
58
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 31, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Oneflow-Inc/libai"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepspeedai/DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference...
helmholtz-analytics/heat
Distributed tensors and Machine Learning framework with GPU and MPI acceleration in Python
hpcaitech/ColossalAI
Making large AI models cheaper, faster and more accessible
horovod/horovod
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
bsc-wdc/dislib
The Distributed Computing library for python implemented using PyCOMPSs programming model for HPC.