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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: rare-puppers
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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: 0.9861111044883728
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+ ---
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+
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+ # rare-puppers
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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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+ #### corgi
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+
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+ ![corgi](images/corgi.jpg)
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+
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+ #### samoyed
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+
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+ ![samoyed](images/samoyed.jpg)
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+
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+ #### shiba inu
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+
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+ ![shiba inu](images/shiba_inu.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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+ "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": "corgi",
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+ "1": "samoyed",
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+ "2": "shiba inu"
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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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+ "corgi": "0",
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+ "samoyed": "1",
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+ "shiba inu": "2"
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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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+ "transformers_version": "4.8.2"
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+ }
images/corgi.jpg ADDED
images/samoyed.jpg ADDED
images/shiba_inu.jpg ADDED
preprocessor_config.json ADDED
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+ {
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+ "do_normalize": true,
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+ "do_resize": true,
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+ "feature_extractor_type": "ViTFeatureExtractor",
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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_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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+ "size": 224
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+ }
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runs/events.out.tfevents.1625226255.622e885341c0.63.0 ADDED
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