- 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
- timm - Hugging Face 文档
timm 是一个包含 SOTA（最先进的）计算机视觉模型、层、实用工具、优化器、调度器、数据加载器、增强方法以及训练 评估脚本的库。 它内置了超过 700 个预训练模型，并且设计得灵活易用。 阅读 快速入门指南，开始上手使用 timm 库。
- 视觉神经网络模型优秀开源工作：timm 库使用方法和代码解读
1 什么是 timm 库？ Py TorchImageModels，简称 timm，是一个巨大的 PyTorch 代码集合，包括了一系列：image modelslayersutilitiesoptimizerssc…
- 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
- 一文详解解读timm的使用方法，从新手变老手 - CSDN博客
timm 是由 Ross Wightman 创建的一个深度学习库，包含了一系列当下最先进（SOTA）的计算机视觉模型、层、工具、优化器、调度器、数据加载器、增强方法，以及用于复现 ImageNet 训练结果的训练 验证脚本。
- Pytorch Image Models (timm) | timmdocs
Pytorch Image Models (timm) `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
- Pytorch Image Models (timm) | timmdocs - GitHub Pages
Pytorch Image Models (timm) `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
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