xiaolai-sqlai/mobilenetv3
xiaolai-sqlai/mobilenetv3 has 1,870 GitHub stars and 345 forks. GitHot measured +1 stars in 24 hours and +2 in 7 days. Last checked 2026-11-11 14:50 UTC. Last push 2023-04-27.
mobilenetv3 with pytorch,provide pre-train model
Measured star growth
- in 24h
- +1
- in 7 days
- +2
- in 15 days
- Collecting history
- in 1 month
- Collecting history
Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.
README.md
OriginalA PyTorch implementation of MobileNetV3
I retrain the mobilenetv3 with some novel tricks and timm. I also provide the train code, pre-training weight and training logs on this project.
You should use torch.load to load the model.
from mobilenetv3 import MobileNetV3_Small, MobileNetV3_Large
# MobileNetV3_Small
net = MobileNetV3_Small()
net.load_state_dict(torch.load("450_act3_mobilenetv3_small.pth", map_location='cpu'))
# MobileNetV3_Large
net = MobileNetV3_Large()
net.load_state_dict(torch.load("450_act3_mobilenetv3_large.pth", map_location='cpu'))
You could reproduce the model by the code.
nohup python -u -m torch.distributed.run --nproc_per_node=8 main.py --model mobilenet_v3_small --epochs 300 --batch_size 256 --lr 4e-3 --update_freq 2 --model_ema false --model_ema_eval false --use_amp true --data_path /data/benchmarks/ILSVRC2012 --output_dir ./checkpoint &
nohup python -u -m torch.distributed.run --nproc_per_node=8 main.py --model mobilenet_v3_small --epochs 450 --batch_size 256 --lr 4e-3 --update_freq 2 --model_ema false --model_ema_eval false --use_amp true --data_path /data/benchmarks/ILSVRC2012 --output_dir ./checkpoint &
nohup python -u -m torch.distributed.run --nproc_per_node=8 main.py --model mobilenet_v3_large --epochs 300 --batch_size 256 --lr 4e-3 --update_freq 2 --model_ema false --model_ema_eval false --use_amp true --data_path /data/benchmarks/ILSVRC2012 --output_dir ./checkpoint &
nohup python -u -m torch.distributed.run --nproc_per_node=8 main.py --model mobilenet_v3_large --epochs 450 --batch_size 256 --lr 4e-3 --update_freq 2 --model_ema false --model_ema_eval false --use_amp true --data_path /data/benchmarks/ILSVRC2012 --output_dir ./checkpoint &
This is a PyTorch implementation of MobileNetV3 architecture as described in the paper Searching for MobileNetV3.
Some details may be different from the original paper, welcome to discuss and help me figure it out.
MobileNetV3
| Madds | Parameters | Top1-acc | |
|---|---|---|---|
| Small (paper) | 66 M | 2.9 M | 67.4% |
| Small (torchvision) | 62 M | 2.5 M | 67.7% |
| Small (our 300 epoch) | 69 M | 3.0 M | 68.9% |
| Small (our 450 epoch) | 69 M | 3.0 M | 69.2% |
| Large (paper) | 219 M | 5.4 M | 75.2% |
| Large (torchvision) | 235 M | 5.5 M | 74.0% |
| Large (our 300 epoch) | 241 M | 5.2 M | 75.6% |
| Large (our 450 epoch) | 241 M | 5.2 M | 75.9% |
Explore related projects
tensorflow/tensorflow
An Open Source Machine Learning Framework for Everyone
201,505 starshuggingface/transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
168,815 starsAUTOMATIC1111/stable-diffusion-webui
Stable Diffusion web UI
165,289 starsComfy-Org/ComfyUI
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. The fastest local inference engine in the world.
146,271 stars