MobilenetV4: add two more lightweight models #2275
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Mobilenetv4 is very fast and ideal for embedded devices. However, for many low-cost, low-power embedded MCU devices, smaller models are required. Hopefully this PR will merge.
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@baorepo if I can get an okay result training one/both of these will merge... FYI I added some REALLY small models recently for test purposes, but they're actually useable for fine-tune on smaller datasets, check out the first three rows of https://github.com/huggingface/pytorch-image-models/blob/main/results/benchmark-infer-amp-nchw-pt240-cu124-rtx4090.csv |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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Thanks, I will also test the small model you mentioned in my scenario. |
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Mobilenetv4 is very fast and ideal for embedded devices. However, for many low-cost, low-power embedded MCU devices, smaller models are required. Hopefully this PR will merge.