Instructions to use aaa12963337/msi-resnet18-pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aaa12963337/msi-resnet18-pretrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="aaa12963337/msi-resnet18-pretrain") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("aaa12963337/msi-resnet18-pretrain") model = AutoModelForImageClassification.from_pretrained("aaa12963337/msi-resnet18-pretrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
25a7cd6
1
Parent(s): ef5d37e
Training in progress, epoch 0
Browse files- config.json +63 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
config.json
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{
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"_name_or_path": "microsoft/resnet-18",
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"architectures": [
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"ResNetForImageClassification"
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],
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"depths": [
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2,
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2,
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2,
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2
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],
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"downsample_in_bottleneck": false,
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"downsample_in_first_stage": false,
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"embedding_size": 64,
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"hidden_act": "relu",
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"hidden_sizes": [
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64,
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128,
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256,
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512
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],
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"id2label": {
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"0": "ADI",
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"1": "BACK",
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"2": "DEB",
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"3": "LYM",
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"4": "MUC",
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"5": "MUS",
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"6": "NORM",
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"7": "STR",
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"8": "TUM"
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},
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"label2id": {
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"ADI": "0",
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"BACK": "1",
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"DEB": "2",
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"LYM": "3",
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"MUC": "4",
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"MUS": "5",
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"NORM": "6",
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"STR": "7",
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"TUM": "8"
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},
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"layer_type": "basic",
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"model_type": "resnet",
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"num_channels": 3,
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"out_features": [
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"stage4"
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],
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"out_indices": [
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4
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],
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"problem_type": "single_label_classification",
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"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4"
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],
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"torch_dtype": "float32",
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"transformers_version": "4.35.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8120ec1dd04ad0ccfcaae90e68520e5cf12b8946969f2a54d0ccf167dae089d8
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size 44778700
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:262cd3b61db9c73d51e91b11217916f8470126ebc65dcba45f475b9d64967927
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size 4155
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