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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%
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