efficientnet-jax

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

? Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Google Brain AutoML

NanoDet-Plus?Super fast and lightweight anchor-free object detection model. ?Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone?

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.