commit files to HF hub

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+images/chk1_fail.jpg filter=lfs diff=lfs merge=lfs -text
+images/chk1_pass.jpg filter=lfs diff=lfs merge=lfs -text
+images/chk2_fail.jpg filter=lfs diff=lfs merge=lfs -text
+images/chk2_pass.jpg filter=lfs diff=lfs merge=lfs -text
+images/chk3_fail.jpg filter=lfs diff=lfs merge=lfs -text
+images/chk3_pass.jpg filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags:
+- image-classification
+- pytorch
+- huggingpics
+metrics:
+- accuracy
+
+model-index:
+- name: krenzcolor_chkpt_classifier
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    metrics:
+      - name: Accuracy
+        type: accuracy
+        value: 0.6428571428571429
+---
+
+# krenzcolor_chkpt_classifier
+
+
+Autogenerated by HuggingPics🤗🖼️
+
+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).
+
+Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
+
+
+## Example Images
+
+
+#### chk1_fail
+
+![chk1_fail](images/chk1_fail.jpg)
+
+#### chk1_pass
+
+![chk1_pass](images/chk1_pass.jpg)
+
+#### chk2_fail
+
+![chk2_fail](images/chk2_fail.jpg)
+
+#### chk2_pass
+
+![chk2_pass](images/chk2_pass.jpg)
+
+#### chk3_fail
+
+![chk3_fail](images/chk3_fail.jpg)
+
+#### chk3_pass
+
+![chk3_pass](images/chk3_pass.jpg)

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "chk1_fail",
+    "1": "chk1_pass",
+    "2": "chk2_fail",
+    "3": "chk2_pass",
+    "4": "chk3_fail",
+    "5": "chk3_pass"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "chk1_fail": "0",
+    "chk1_pass": "1",
+    "chk2_fail": "2",
+    "chk2_pass": "3",
+    "chk3_fail": "4",
+    "chk3_pass": "5"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.21.3"
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "ViTFeatureExtractor",
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "size": 224
+}

pytorch_model.bin

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