deit | Official DeiT repository | Machine Learning library

by facebookresearch Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | deit Summary

deit is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Transformer applications. deit has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

This repository contains PyTorch evaluation code, training code and pretrained models for the following projects:.

Support

Quality

Security

License

Reuse

Support

deit has a medium active ecosystem.

It has 3417 star(s) with 511 fork(s). There are 48 watchers for this library.

It had no major release in the last 6 months.

There are 10 open issues and 173 have been closed. On average issues are closed in 75 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of deit is current.

Quality

deit has no bugs reported.

Security

deit has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

deit is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

deit releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed deit and discovered the below as its top functions. This is intended to give you an instant insight into deit implemented functionality, and help decide if they suit your requirements.

Argument parser .
Train one epoch .
Compute the loss .
Prints each object in iterable .
Parse arguments .
Generate new dataaugator .
Build a transform .
Evaluate the model .
init distributed mode
Resml pth model .

Get all kandi verified functions for this library.

deit Key Features

No Key Features are available at this moment for deit.

deit Examples and Code Snippets

SOTA Image Classification Models in PyTorch, Usage

Python

Lines of Code : 156

License : Permissive (MIT)

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$ python tools/show.py

Model Names    Model Variants
-------------  --------------------------------
ResNet         ['18', '34', '50', '101', '152']
MicroNet       ['M1', 'M2', 'M3']
ConvNeXt       ['T', 'S', 'M']
GFNet          ['T', 'S', 'B']
PVTv

PLSC (Paddle Large Scale Classification),10. Demo

Python

Lines of Code : 44

License : No License

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# Create models directory
mkdir -p models

# Download blazeface face detection model and extract it
wget https://paddle-model-ecology.bj.bcebos.com/model/insight-face/blazeface_fpn_ssh_1000e_v1.0_infer.tar -P models/
tar -xzf models/blazeface_fpn_ssh

Usage

Python

Lines of Code : 20

License : Permissive (Apache-2.0)

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pytorch >= 1.6.0
torchvision >= 0.7.0
timm >= 0.3.4
apex == 0.1.0

import torch
from resnet_pf import resnet50_hybrid

model = resnet50_hybrid() 
model.load_state_dict(torch.load('./weight/checkpoint.pth'))
print(model(torch.randn(1, 3, 224,

Community Discussions

Trending Discussions on deit

How to safely type hierarchical metadata objects in TypeScript?

QUESTION

How to safely type hierarchical metadata objects in TypeScript?

Asked 2020-Jun-26 at 01:22

I'd like to create some constants that define a hierarchy of categories with subcategories. These will then be re-used to render different pages in an application, but by defining them as constants in one place I can quickly scaffold pages.

For example, given categories like:

...

ANSWER

Answered 2020-Jun-26 at 01:22

In cases like this I usually make a helper function which verifies that a value is assignable to a type without widening it to that type. Assuming CATEGORIES looks like

Source https://stackoverflow.com/questions/62583999

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install deit

You can download it from GitHub.
You can use deit like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.