πŸ› οΈ
Pytorch Image Models tool by huggingface
⭐ 50.5
πŸ› οΈ
Tool

Pytorch Image Models

by huggingface huggingface/pytorch-image-models
Free2AITools Nexus Index
50.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 62
P: Popularity 74
R: Recency 100
Q: Quality 70
Tech Context
Vital Performance —
Source β†’
Python Lang
Open Source 37.2K Stars
Alpha Reliability
Tool Information Summary
Entity Passport
Registry ID huggingface/pytorch-image-models
License Apache-2.0
Provider github
πŸ“œ

Cite this tool

Academic & Research Attribution

BibTeX 
@misc{gh_tool_huggingface_pytorch_image_models,
  author = {huggingface},
  title = {Pytorch Image Models Tool},
  year = {2019},
  howpublished = {\url{https://github.com/huggingface/pytorch-image-models}},
  note = {Accessed via Free2AITools.}
}
APA Style
huggingface. (2019). Pytorch Image Models [Tool]. Free2AITools. https://github.com/huggingface/pytorch-image-models

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ™ GitHub Clone
git clone https://github.com/huggingface/pytorch-image-models
🐍 PIP Install
pip install pytorch-image-models

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 62
Popularity (P) 74
Recency (R) 100
Quality (Q) 70

πŸ’¬ Index Insight

FNI V2.0 for Pytorch Image Models: Authority (A:62), Popularity (P:74), Recency (R:100), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data

πŸ“‹ Specs

Language
Python
License
Apache-2.0
Version
β€”
Explore Source Node

Technical Documentation

PyTorch Image Models

What's New

September 10-11, 2026

  • Add Qwen3-VL / Qwen3.5 / Qwen3.8 ViT classifier and encoder variants, including classifiers w/ and w/o the native spatial merger.
  • Add Sapiens2 ViTs with EVA and NaFlexViT support. Both model additions include native timm Hub weights. Thanks Yonghye Kwon.
  • Add iFormer with native timm Hub weights. Thanks Ryan Hou.
  • Add EfficientViM with native timm Hub weights. Thanks smellslikeml.
  • Add DeepSeek-V4 / V4.1 ViT classifiers and encoders with native timm Hub weights. Thanks Yonghye Kwon.
  • Switch default NaFlex SigLIP position interpolation, inference.py input-size selection, and improve --model-kwargs parsing.
  • Fix meta-device construction and device/dtype factory support for a few models; move config tests to meta for faster CI, meta context coverage.

August 27, 2026

  • Add LowFormer model and weights
  • Fix or merge a host of real but small or not commonly encountered bugs surfaced by agents
  • Release 1.0.29

August 11, 2026

  • Add model defs and pretrained weights for
  • Add per-batch image and batch size scheduling for non-NaFlex training, including progressive small-to-large resolution s

Social Proof

GitHub Repository
37.2KStars
5.2KForks
Repo Issues
πŸ™ Data Source: GitHub β†—
πŸ”„ Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Tool Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
gh-tool--huggingface--pytorch-image-models
slug
huggingface--pytorch-image-models
source
github
author
huggingface
license
Apache-2.0
tags
pytorch, resnet, pretrained-models, pretrained-weights, distributed-training, mobile-deep-learning, mobilenet-v2, mobilenetv3, efficientnet, augmix, randaugment, mixnet, vision-transformer-models, nfnets, normalization-free-training, maxvit, convnext, image-classification, imagenet, optimizer, python

βš™οΈ Technical Specs

pipeline tag
other

πŸ“Š Engagement & Metrics

downloads
0
stars
37,160
forks
5,196
github stars
37,160

Data indexed from public sources. Updated daily.