add Core ML model

README.md

@@ -1,3 +1,15 @@
 ---
 license: apache-2.0
+tags:
+- vision
+- image-classification
+datasets:
+- imagenet
+- imagenet-21k
 ---
+
+# Vision Transformer (base-sized model) 
+
+Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Dosovitskiy et al. and first released in [this repository](https://github.com/google-research/vision_transformer). However, the weights were converted from the [timm repository](https://github.com/rwightman/pytorch-image-models) by Ross Wightman, who already converted the weights from JAX to PyTorch. Credits go to him. 
+
+This repo contains a Core ML version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224).

ViT.mlpackage/Data/com.apple.CoreML/weights/weight.bin

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+oid sha256:08a336a182020c086698701ace4004323b245446fe4d253a4f28e3981d80eb08
+size 346283520

ViT.mlpackage/Manifest.json

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+{
+    "fileFormatVersion": "1.0.0",
+    "itemInfoEntries": {
+        "DF6797D3-1EF1-4BE9-92AB-E2090CAC5261": {
+            "author": "com.apple.CoreML",
+            "description": "CoreML Model Specification",
+            "name": "model.mlmodel",
+            "path": "com.apple.CoreML/model.mlmodel"
+        },
+        "EF1973A9-D608-4DEB-A9C5-13BFDAF43AFD": {
+            "author": "com.apple.CoreML",
+            "description": "CoreML Model Weights",
+            "name": "weights",
+            "path": "com.apple.CoreML/weights"
+        }
+    },
+    "rootModelIdentifier": "DF6797D3-1EF1-4BE9-92AB-E2090CAC5261"
+}