commit files to HF hub

.gitattributes

@@ -33,3 +33,13 @@ 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
+images/cat.jpg filter=lfs diff=lfs merge=lfs -text
+images/cow.jpg filter=lfs diff=lfs merge=lfs -text
+images/dog.jpg filter=lfs diff=lfs merge=lfs -text
+images/dolphin.jpg filter=lfs diff=lfs merge=lfs -text
+images/eagle.jpg filter=lfs diff=lfs merge=lfs -text
+images/giant_panda.jpg filter=lfs diff=lfs merge=lfs -text
+images/horse.jpg filter=lfs diff=lfs merge=lfs -text
+images/monkey.jpg filter=lfs diff=lfs merge=lfs -text
+images/sheep.jpg filter=lfs diff=lfs merge=lfs -text
+images/spider.jpg filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags:
+- image-classification
+- pytorch
+- huggingpics
+metrics:
+- accuracy
+
+model-index:
+- name: 10-animals-classification
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    metrics:
+      - name: Accuracy
+        type: accuracy
+        value: 0.9911110997200012
+---
+
+# 10-animals-classification
+
+
+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
+
+
+#### cat
+
+![cat](images/cat.jpg)
+
+#### cow
+
+![cow](images/cow.jpg)
+
+#### dog
+
+![dog](images/dog.jpg)
+
+#### dolphin
+
+![dolphin](images/dolphin.jpg)
+
+#### eagle
+
+![eagle](images/eagle.jpg)
+
+#### giant panda
+
+![giant panda](images/giant_panda.jpg)
+
+#### horse
+
+![horse](images/horse.jpg)
+
+#### monkey
+
+![monkey](images/monkey.jpg)
+
+#### sheep
+
+![sheep](images/sheep.jpg)
+
+#### spider
+
+![spider](images/spider.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": "cat",
+    "1": "cow",
+    "2": "dog",
+    "3": "dolphin",
+    "4": "eagle",
+    "5": "giant panda",
+    "6": "horse",
+    "7": "monkey",
+    "8": "sheep",
+    "9": "spider"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "cat": "0",
+    "cow": "1",
+    "dog": "2",
+    "dolphin": "3",
+    "eagle": "4",
+    "giant panda": "5",
+    "horse": "6",
+    "monkey": "7",
+    "sheep": "8",
+    "spider": "9"
+  },
+  "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": "4.31.0"
+}

preprocessor_config.json

@@ -0,0 +1,22 @@
+{
+  "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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+size 343290541

runs/events.out.tfevents.1690619563.612207602d31.436.0

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