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commit files to HF hub

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README.md ADDED
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+ ---
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+ tags:
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+ - image-classification
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+ - pytorch
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+ - huggingpics
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+ metrics:
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+ - accuracy
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+
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+ model-index:
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+ - name: refigerator_items
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.17469879984855652
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+ ---
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+
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+ # refigerator_items
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+
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+
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+ Autogenerated by HuggingPics🤗🖼️
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+
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+ Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
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+
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+ Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
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+
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+
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+ ## Example Images
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+
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+
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+ #### banana
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+
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+ ![banana](images/banana.jpg)
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+
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+ #### bread
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+
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+ ![bread](images/bread.jpg)
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+
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+ #### eggs
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+
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+ ![eggs](images/eggs.jpg)
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+
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+ #### milk
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+
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+ ![milk](images/milk.jpg)
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+
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+ #### potato
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+
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+ ![potato](images/potato.jpg)
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+
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+ #### spinach
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+
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+ ![spinach](images/spinach.jpg)
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+
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+ #### tomato
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+
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+ ![tomato](images/tomato.jpg)
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224-in21k",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "encoder_stride": 16,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "banana",
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+ "1": "bread",
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+ "2": "eggs",
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+ "3": "milk",
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+ "4": "potato",
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+ "5": "spinach",
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+ "6": "tomato",
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+ "7": "train",
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+ "8": "val"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "banana": "0",
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+ "bread": "1",
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+ "eggs": "2",
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+ "milk": "3",
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+ "potato": "4",
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+ "spinach": "5",
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+ "tomato": "6",
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+ "train": "7",
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+ "val": "8"
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.28.1"
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+ }
preprocessor_config.json ADDED
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+ {
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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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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "image_processor_type": "ViTFeatureExtractor",
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+ "image_std": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "resample": 2,
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+ "rescale_factor": 0.00392156862745098,
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+ "size": {
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+ "height": 224,
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+ "width": 224
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+ }
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+ }
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