micromind/ImageNet

After logging in on your machine, you can download the checkpoints:

from huggingface_hub import hf_hub_download

REPO_ID = "micromind/ImageNet"
FILENAME = "v5/state_dict.pth.tar"

model_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)

followed by:

model = PhiNet(
    input_shape=(3, 224, 224),
    alpha=...,
    num_layers=...,
    beta=...,
    t_zero=...,
    include_top=True,
    num_classes=1000,
    compatibility=False,
    divisor=8,
    downsampling_layers=[4,5,7]
)

model.load_state_dict(torch.load(model_path))

Note for v1, when initializing the network, use:

downsampling_layers=[5,7]

Performance:

Model name	Acc@1	Acc@5
v1	71.18%	89.65%
v2	65.21%	85.82%
v3	64.69%	86.15%
v5	67.99%	87.53%
v6	61.86%	83.44%
v7	53.66%	77.13%