lewtun HF staff commited on
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commit files to HF hub

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.gitattributes CHANGED
@@ -25,3 +25,5 @@ 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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+ images/crispy_fried_chicken.jpg filter=lfs diff=lfs merge=lfs -text
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+ images/poodle.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: dog-vs-chicken
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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: 1.0
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+ ---
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+
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+ # dog-vs-chicken
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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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+ #### crispy fried chicken
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+
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+ ![crispy fried chicken](images/crispy_fried_chicken.jpg)
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+
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+ #### poodle
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+
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+ ![poodle](images/poodle.jpg)
config.json ADDED
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+ "ViTForImageClassification"
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+ "attention_probs_dropout_prob": 0.0,
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+ "encoder_stride": 16,
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+ "id2label": {
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+ "0": "crispy fried chicken",
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+ "crispy fried chicken": "0",
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+ "poodle": "1"
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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": "4.19.4"
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+ }
images/crispy_fried_chicken.jpg ADDED

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