- timm (PyTorch Image Models) - Hugging Face
Py T orch Im age M odels (timm) is a collection of image models, layers, utilities, optimizers, schedulers, data-loaders augmentations, and reference training validation scripts that aim to pull together a wide variety of SOTA models with ability to reproduce ImageNet training results
- huggingface pytorch-image-models - GitHub
Py T orch Im age M odels (timm) is a collection of image models, layers, utilities, optimizers, schedulers, data-loaders augmentations, and reference training validation scripts that aim to pull together a wide variety of SOTA models with ability to reproduce ImageNet training results
- Pytorch Image Models (timm) | timmdocs
`timm` is a deep-learning library created by Ross Wightman and is a collection of SOTA computer vision models, layers, utilities, optimizers, schedulers, data-loaders, augmentations and also training validating scripts with ability to reproduce ImageNet training results
- GitHub - pprp timm: PyTorch image models, scripts, pretrained weights . . .
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3 V2, RegNet, DPN, CSPNet, and more - pprp timm
- timm · PyPI
Py T orch Im age M odels (timm) is a collection of image models, layers, utilities, optimizers, schedulers, data-loaders augmentations, and reference training validation scripts that aim to pull together a wide variety of SOTA models with ability to reproduce ImageNet training results
- timm - Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science
- Using timm at Hugging Face
timm, also known as pytorch-image-models, is an open-source collection of state-of-the-art PyTorch image models, pretrained weights, and utility scripts for training, inference, and validation
- Installation - Hugging Face
Before you start, you’ll need to setup your environment and install the appropriate packages timm is tested on Python 3+ You should install timm in a virtual environment to keep things tidy and avoid dependency conflicts
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