commit files to HF hub

.gitattributes

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 *.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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README.md

@@ -0,0 +1,128 @@
+---
+tags:
+- image-classification
+- pytorch
+- huggingpics
+metrics:
+- accuracy
+
+model-index:
+- name: Sign-Language
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    metrics:
+      - name: Accuracy
+        type: accuracy
+        value: 1.0
+---
+
+# Sign-Language
+
+
+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
+
+
+#### A
+
+![A](images/A.jpg)
+
+#### B
+
+![B](images/B.jpg)
+
+#### C
+
+![C](images/C.jpg)
+
+#### D
+
+![D](images/D.jpg)
+
+#### E
+
+![E](images/E.jpg)
+
+#### F
+
+![F](images/F.jpg)
+
+#### G
+
+![G](images/G.jpg)
+
+#### H
+
+![H](images/H.jpg)
+
+#### I
+
+![I](images/I.jpg)
+
+#### K
+
+![K](images/K.jpg)
+
+#### L
+
+![L](images/L.jpg)
+
+#### M
+
+![M](images/M.jpg)
+
+#### N
+
+![N](images/N.jpg)
+
+#### O
+
+![O](images/O.jpg)
+
+#### P
+
+![P](images/P.jpg)
+
+#### Q
+
+![Q](images/Q.jpg)
+
+#### R
+
+![R](images/R.jpg)
+
+#### S
+
+![S](images/S.jpg)
+
+#### T
+
+![T](images/T.jpg)
+
+#### U
+
+![U](images/U.jpg)
+
+#### V
+
+![V](images/V.jpg)
+
+#### W
+
+![W](images/W.jpg)
+
+#### X
+
+![X](images/X.jpg)
+
+#### Y
+
+![Y](images/Y.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": "A",
+    "1": "B",
+    "10": "L",
+    "11": "M",
+    "12": "N",
+    "13": "O",
+    "14": "P",
+    "15": "Q",
+    "16": "R",
+    "17": "S",
+    "18": "T",
+    "19": "U",
+    "2": "C",
+    "20": "V",
+    "21": "W",
+    "22": "X",
+    "23": "Y",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "K"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "A": "0",
+    "B": "1",
+    "C": "2",
+    "D": "3",
+    "E": "4",
+    "F": "5",
+    "G": "6",
+    "H": "7",
+    "I": "8",
+    "K": "9",
+    "L": "10",
+    "M": "11",
+    "N": "12",
+    "O": "13",
+    "P": "14",
+    "Q": "15",
+    "R": "16",
+    "S": "17",
+    "T": "18",
+    "U": "19",
+    "V": "20",
+    "W": "21",
+    "X": "22",
+    "Y": "23"
+  },
+  "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": "4.25.1"
+}

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": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

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