Instructions to use SamAdamDay/resnet18_cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use SamAdamDay/resnet18_cifar10 with timm:
import timm model = timm.create_model("hf_hub:SamAdamDay/resnet18_cifar10", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Add model
Browse files- config.json +47 -10
- model.safetensors +1 -1
- pytorch_model.bin +1 -1
config.json
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@@ -7,8 +7,8 @@
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"custom_load": false,
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"input_size": [
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3,
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-
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],
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"test_input_size": [
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3,
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"test_crop_pct": 1.0,
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"crop_mode": "center",
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"mean": [
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0.
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0.
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0.
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],
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"std": [
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0.
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],
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"num_classes":
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"pool_size": [
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7,
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7
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"classifier": "fc",
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"origin_url": "https://github.com/huggingface/pytorch-image-models",
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"paper_ids": "arXiv:2110.00476"
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}
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}
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"custom_load": false,
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"input_size": [
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3,
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256,
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256
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],
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"test_input_size": [
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3,
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"test_crop_pct": 1.0,
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"crop_mode": "center",
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"mean": [
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0.49139968,
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0.4821582,
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0.44653124
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],
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"std": [
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+
0.24703233,
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0.24348505,
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+
0.26158768
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],
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"num_classes": 10,
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"pool_size": [
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7,
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7
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"classifier": "fc",
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"origin_url": "https://github.com/huggingface/pytorch-image-models",
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"paper_ids": "arXiv:2110.00476"
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},
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"hf_hub_id": "SamAdamDay/resnet18_cifar10",
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"source": "hf-hub",
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"tag": "a1_in1k",
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"custom_load": false,
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"input_size": [
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3,
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256,
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256
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],
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"test_input_size": [
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3,
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288,
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288
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],
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"fixed_input_size": false,
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"interpolation": "bicubic",
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"crop_pct": 0.95,
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"test_crop_pct": 1.0,
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"crop_mode": "center",
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"mean": [
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0.49139968,
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+
0.4821582,
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+
0.44653124
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],
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"std": [
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+
0.24703233,
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0.24348505,
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0.26158768
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],
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"pool_size": [
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7,
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7
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],
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"first_conv": "conv1",
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"classifier": "fc",
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"origin_url": "https://github.com/huggingface/pytorch-image-models",
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"paper_ids": "arXiv:2110.00476"
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}
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model.safetensors
CHANGED
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version https://git-lfs.github.com/spec/v1
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size 44775880
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version https://git-lfs.github.com/spec/v1
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size 44775880
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pytorch_model.bin
CHANGED
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version https://git-lfs.github.com/spec/v1
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size 44805426
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version https://git-lfs.github.com/spec/v1
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size 44805426
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