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JAX - A curated list of resources https://github.com/google/jax
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python ⚡
ALBERT model Pretraining and Fine Tuning using TF2.0
TensorFlow wheels built for latest CUDA/CuDNN and enabled performance flags: SSE, AVX, FMA; XLA
S + Autograd + XLA :: S-parameter based frequency domain circuit simulations and optimizations using JAX.
基于tensorflow1.x的预训练模型调用,支持单机多卡、梯度累积,XLA加速,混合精度。可灵活训练、验证、预测。
PyTorch distributed training acceleration framework
Presents comprehensive benchmarks of XLA-compatible pre-trained models in Keras.
XLA integration of Open Neural Network Exchange (ONNX)