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Home Page: http://detectors.readthedocs.io/
License: Apache License 2.0
Package to accelerate research on generalized out-of-distribution (OOD) detection.
Home Page: http://detectors.readthedocs.io/
License: Apache License 2.0
Hi @edadaltocg thanks for sharing the codes. How to inference of cifar10 test set via your pretrained models?
I'm trying to load and normally evaluate with resent18_cifar10
. I have a VRAM 16 and Memory 64. No matter what eval batch size I use, eventually this throw an Out-of-Memory error!
import detectors
import timm
model = timm.create_model("resnet18_cifar10", pretrained=True)
But when I use timm from hf and even batch size 1024 it's not throwing memory error. Any thought?
import timm
m = timm.create_model('resnet18', pretrained=True, num_classes=10)
Thank you
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