Python EfficientNetV2-with-TPU Resources

Easy-Translate is a script for translating large text files in your machine using the M2M100 models from Facebook/Meta AI. We also privide a script fo

ML_Notebooks Collection of machine learning related notebooks to share. Notebooks GAN_distributed_training.ipynb In this Notebook, TensorFlow's tutori

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Cloud TPUs This repository is a collection of reference models and tools used with Cloud TPUs. The fastest way to get started training a model on a Cl

Enformer TPU training script (wip) The full training script for Enformer (Tensorflow Sonnet) on TPU clusters, in an effort to migrate the model to pyt

EfficientNetV2-with-TPU EfficientNet EfficientNetV2 adalah jenis jaringan saraf convolutional yang memiliki kecepatan pelatihan lebih cepat dan efisie

NeRF Minimal Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. Result of Tiny-NeRF RGB Depth

Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac

Class-Balanced Loss Based on Effective Number of Samples Tensorflow code for the paper: Class-Balanced Loss Based on Effective Number of Samples Yin C

AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil

PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe

Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac

EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor

Pretrain and Fine-tune a T5 model with Flax on GCP This tutorial details how pretrain and fine-tune a FlaxT5 model from HuggingFace using a TPU VM ava

Text-to-Image Translation (DALL-E) for TPU in Pytorch Refactoring Taming Transformers and DALLE-pytorch for TPU VM with Pytorch Lightning Requirements

FunMatch-Distillation TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A g

Sharpness-Aware-Minimization-TensorFlow This repository provides a minimal implementation of sharpness-aware minimization (SAM) (Sharpness-Aware Minim

EfficientNetV2-S implementation using PyTorch Train Steps Configure imagenet path by changing data_dir in train.py python main.py --benchmark for mode

EfficientNetv2_TensorRT_int8 EfficientNetv2模型实现来自https://github.com/d-li14/efficientnetv2.pytorch 环境配置 ubuntu：18.04 cuda：11.0 cudnn：8.0 tensorrt：7

🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.

[NEW!] Check out our latest work involution accepted to CVPR'21 that introduces a new neural operator, other than convolution and self-attention. PyTo

Smart Social Distancing Smart Social Distancing Introduction Getting Started Prerequisites Usage Processor Optional Parameters Configuring AWS credent

JAX: Autograd and XLA Quickstart | Transformations | Install guide | Neural net libraries | Change logs | Reference docs | Code search News: JAX tops

JAX: Autograd and XLA Quickstart | Transformations | Install guide | Neural net libraries | Change logs | Reference docs | Code search News: JAX tops