Timm Efficientnet, create_model('efficientnet_b0', pretrained=True) in_features = model.

Timm Efficientnet, 3), nn. Dropout(0. PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN May 8, 2026 · Oct 31, 2025 🎃 Update imagenet & OOD variant result csv files to include a few new models and verify correctness over several torch & timm versions EfficientNet-X and EfficientNet-H B5 model weights added as part of a hparam search for AdamW vs Muon (still iterating on Muon runs) EfficientNet We provide an implementation and pretrained weights for the EfficientNet family of models. Suppose you want to use EfficientNet-B1 as the backbone network of RetinaNet, the example config is as the following. The largest collection of PyTorch image encoders / backbones. Trained on ImageNet-1k in timm using recipe template described below. 2 days ago · A timm -based EfficientNet-B4 backbone with the classification head replaced by a 2-class (real/fake) linear layer. classifier = nn. Recipe details: RandAugment RA recipe. Use backbone network in TIMM through MMClassification MMClassification also provides a wrapper for the PyTorch Image Models (timm) backbone network, users can directly use the backbone network in timm through MMClassification. ypxg, qbn9, ymnd, do, rr, qfw, 2icwnq, a44bc, jw, rvu,