commit files to HF hub

.gitattributes

@@ -33,3 +33,23 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
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+images/Blouse.jpg filter=lfs diff=lfs merge=lfs -text
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+images/Hat.jpg filter=lfs diff=lfs merge=lfs -text
+images/Hoodie.jpg filter=lfs diff=lfs merge=lfs -text
+images/Longsleeve.jpg filter=lfs diff=lfs merge=lfs -text
+images/Not_sure.jpg filter=lfs diff=lfs merge=lfs -text
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+images/Undershirt.jpg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,112 @@
+---
+tags:
+- image-classification
+- pytorch
+- huggingpics
+metrics:
+- accuracy
+
+model-index:
+- name: rare-puppers
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    metrics:
+      - name: Accuracy
+        type: accuracy
+        value: 0.8345679044723511
+---
+
+# rare-puppers
+
+
+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
+
+
+#### Blazer
+
+![Blazer](images/Blazer.jpg)
+
+#### Blouse
+
+![Blouse](images/Blouse.jpg)
+
+#### Body
+
+![Body](images/Body.jpg)
+
+#### Dress
+
+![Dress](images/Dress.jpg)
+
+#### Hat
+
+![Hat](images/Hat.jpg)
+
+#### Hoodie
+
+![Hoodie](images/Hoodie.jpg)
+
+#### Longsleeve
+
+![Longsleeve](images/Longsleeve.jpg)
+
+#### Not sure
+
+![Not sure](images/Not_sure.jpg)
+
+#### Other
+
+![Other](images/Other.jpg)
+
+#### Outwear
+
+![Outwear](images/Outwear.jpg)
+
+#### Pants
+
+![Pants](images/Pants.jpg)
+
+#### Polo
+
+![Polo](images/Polo.jpg)
+
+#### Shirt
+
+![Shirt](images/Shirt.jpg)
+
+#### Shoes
+
+![Shoes](images/Shoes.jpg)
+
+#### Shorts
+
+![Shorts](images/Shorts.jpg)
+
+#### Skip
+
+![Skip](images/Skip.jpg)
+
+#### Skirt
+
+![Skirt](images/Skirt.jpg)
+
+#### T-Shirt
+
+![T-Shirt](images/T-Shirt.jpg)
+
+#### Top
+
+![Top](images/Top.jpg)
+
+#### Undershirt
+
+![Undershirt](images/Undershirt.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": "Blazer",
+    "1": "Blouse",
+    "10": "Pants",
+    "11": "Polo",
+    "12": "Shirt",
+    "13": "Shoes",
+    "14": "Shorts",
+    "15": "Skip",
+    "16": "Skirt",
+    "17": "T-Shirt",
+    "18": "Top",
+    "19": "Undershirt",
+    "2": "Body",
+    "3": "Dress",
+    "4": "Hat",
+    "5": "Hoodie",
+    "6": "Longsleeve",
+    "7": "Not sure",
+    "8": "Other",
+    "9": "Outwear"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Blazer": "0",
+    "Blouse": "1",
+    "Body": "2",
+    "Dress": "3",
+    "Hat": "4",
+    "Hoodie": "5",
+    "Longsleeve": "6",
+    "Not sure": "7",
+    "Other": "8",
+    "Outwear": "9",
+    "Pants": "10",
+    "Polo": "11",
+    "Shirt": "12",
+    "Shoes": "13",
+    "Shorts": "14",
+    "Skip": "15",
+    "Skirt": "16",
+    "T-Shirt": "17",
+    "Top": "18",
+    "Undershirt": "19"
+  },
+  "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": "4.38.2"
+}

model.safetensors

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+size 343279344

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
+  }
+}

runs/events.out.tfevents.1711619624.d46d8aa3b3e9.768.0

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