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README.md

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+---
+library_name: transformers
+pipeline_tag: image-feature-extraction
+tags:
+- dino
+- self-supervised
+- vision-transformer
+- food101
+datasets:
+- ethz/food101
+---
+
+# DINOv1-ViT-S-16-food101
+
+DINOv1 ViT-S/16 model trained from scratch on the Food-101 dataset using a custom training [repo](https://github.com/mnjm/dino).
+
+## Evaluation
+
+Weighted k-NN evaluation on Food-101 validation features:
+
+| k | Top-1 accuracy | Top-5 accuracy |
+| --- | --- | --- |
+| 5 | 64.09% | 79.93% |
+| 10 | 66.38% | 83.47% |
+| 20 | 67.59% | 86.17% |
+| 100 | 67.81% | 88.72% |
+
+## Run
+
+```python
+from transformers import AutoImageProcessor, ViTModel
+
+processor = AutoImageProcessor.from_pretrained("mnjm/DINOv1-ViT-S-16-food101")
+model = ViTModel.from_pretrained("mnjm/DINOv1-ViT-S-16-food101")
+inputs = processor(images=image, return_tensors="pt")
+outputs = model(**inputs)
+image_features = outputs.last_hidden_state[:, 0]
+```

config.json

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+{
+  "architectures": [
+    "ViTModel"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "dtype": "float32",
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 384,
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-05,
+  "model_type": "vit",
+  "num_attention_heads": 6,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "pooler_act": "tanh",
+  "pooler_output_size": 384,
+  "qkv_bias": true,
+  "transformers_version": "5.14.1"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9dcba56ede86cd3d9861ad8476163bfc66e9a0ea02dd9200cc1de464f9eda2b2
+size 86684608

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

raw_checkpoint.zip

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+size 460127254