commit files to HF hub

.gitattributes

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 *tfevents* filter=lfs diff=lfs merge=lfs -text
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+images/10-19.jpg filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+tags:
+- image-classification
+- pytorch
+- huggingpics
+metrics:
+- accuracy
+
+model-index:
+- name: Age_Classify_v001
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    metrics:
+      - name: Accuracy
+        type: accuracy
+        value: 0.5719775557518005
+---
+
+# Age_Classify_v001
+
+
+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
+
+
+#### 0-2
+
+![0-2](images/0-2.jpg)
+
+#### 10-19
+
+![10-19](images/10-19.jpg)
+
+#### 20-29
+
+![20-29](images/20-29.jpg)
+
+#### 3-9
+
+![3-9](images/3-9.jpg)
+
+#### 30-39
+
+![30-39](images/30-39.jpg)
+
+#### 40-49
+
+![40-49](images/40-49.jpg)
+
+#### 50-59
+
+![50-59](images/50-59.jpg)
+
+#### 60-69
+
+![60-69](images/60-69.jpg)
+
+#### 70-79
+
+![70-79](images/70-79.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": "0-2",
+    "1": "10-19",
+    "2": "20-29",
+    "3": "3-9",
+    "4": "30-39",
+    "5": "40-49",
+    "6": "50-59",
+    "7": "60-69",
+    "8": "70-79"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0-2": "0",
+    "10-19": "1",
+    "20-29": "2",
+    "3-9": "3",
+    "30-39": "4",
+    "40-49": "5",
+    "50-59": "6",
+    "60-69": "7",
+    "70-79": "8"
+  },
+  "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": "4.27.4"
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTFeatureExtractor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

pytorch_model.bin

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runs/events.out.tfevents.1681794500.chris04.4050351.0

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