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commit files to HF hub

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.gitattributes CHANGED
@@ -25,3 +25,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zstandard filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zstandard filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ images/Don_Julio.jpg filter=lfs diff=lfs merge=lfs -text
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+ images/Jack_Daniels.jpg filter=lfs diff=lfs merge=lfs -text
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+ images/Southern_Comfort.jpg filter=lfs diff=lfs merge=lfs -text
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+ images/bacardi.jpg filter=lfs diff=lfs merge=lfs -text
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+ images/johnny_walker.jpg filter=lfs diff=lfs merge=lfs -text
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-bottle
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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: 0.6770833134651184
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+ ---
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+
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+ # rare-bottle
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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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+ #### Don Julio
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+
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+ ![Don Julio](images/Don_Julio.jpg)
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+
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+ #### Jack Daniels
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+
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+ ![Jack Daniels](images/Jack_Daniels.jpg)
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+
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+ #### Southern Comfort
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+
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+ ![Southern Comfort](images/Southern_Comfort.jpg)
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+
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+ #### bacardi
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+
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+ ![bacardi](images/bacardi.jpg)
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+
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+ #### johnny walker
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+
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+ ![johnny walker](images/johnny_walker.jpg)
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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": "Don Julio",
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+ "1": "Jack Daniels",
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+ "2": "Southern Comfort",
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+ "3": "bacardi",
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+ },
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+ "johnny walker": "4"
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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": "4.20.1"
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+ }
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