Instructions to use ahmedesmail16/Project_Class_Model_beit-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedesmail16/Project_Class_Model_beit-base-patch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmedesmail16/Project_Class_Model_beit-base-patch16") 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("ahmedesmail16/Project_Class_Model_beit-base-patch16") model = AutoModelForImageClassification.from_pretrained("ahmedesmail16/Project_Class_Model_beit-base-patch16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 0
Browse files
config.json
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{
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"_name_or_path": "microsoft/resnet-50",
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"architectures": [
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"ResNetForImageClassification"
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],
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"depths": [
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3,
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4,
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6,
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3
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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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256,
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512,
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1024,
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2048
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],
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"id2label": {
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"0": "Erythromelal",
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"1": "Guttate",
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"2": "Inverse",
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"3": "Nail",
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"4": "Normal",
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"5": "Plaque",
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"6": "Pustular"
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},
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"label2id": {
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"Erythromelal": 0,
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"Guttate": 1,
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"Inverse": 2,
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"Nail": 3,
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"Normal": 4,
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"Plaque": 5,
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"Pustular": 6
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},
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"layer_type": "bottleneck",
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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": "4.38.2"
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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:c4715292e4897f192ebe9a1c6dc046482b800c505df154dfb7d6dda2da10154f
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size 94343948
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preprocessor_config.json
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{
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"crop_pct": 0.875,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "ConvNextImageProcessor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 224
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}
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}
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runs/Apr06_22-32-40_fa9f3e5e02dd/events.out.tfevents.1712442767.fa9f3e5e02dd.367.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:8fbae84c7f81284892085cbf74f48e8d5ae11c2469d837328d6de8b8aa6207a1
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size 5225
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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:ddf032dfb73873a2cf6c0ae5120dd9edb516b6189bccb499adec7ad124946db5
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size 4920
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