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README.md

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+---
+language: en
+tags:
+- image-classification
+- vision-transformer
+- protovit
+- pins
+license: mit
+---
+
+# ProtoViT Model - deit_small_patch16_224 (PINS)
+
+This is a fine-tuned deit_small_patch16_224 model trained on Pinterest Face Recognition Dataset from the paper ["Interpretable Image Classification with Adaptive Prototype-based Vision Transformers"](https://arxiv.org/abs/2410.20722).
+
+## Model Details
+
+- Base architecture: deit_small_patch16_224
+- Dataset: Pinterest Face Recognition Dataset
+- Number of classes: 155
+- Fine-tuned checkpoint: `14finetuned0.8042`
+- Accuracy: 80.42%
+
+## Training Details
+
+- Number of prototypes: 2000
+- Prototype size: 1×1
+- Training process: Warm up → Joint training → Push → Last layer fine-tuning
+- Weight coefficients:
+  - Cross entropy: 1.0
+  - Clustering: -0.8
+  - Separation: 0.1
+  - L1: 0.01
+  - Orthogonal: 0.001
+  - Coherence: 0.003
+- Training set size: 70420
+- Push set size: 13979
+- Test set size: 3555
+- Batch size: 128
+
+## Dataset Description
+
+A face recognition dataset collected from Pinterest containing 155 different identity classes
+Dataset link: https://www.kaggle.com/datasets/hereisburak/pins-face-recognition
+
+## Usage
+
+```python
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+
+# Load model and processor
+model = AutoModelForImageClassification.from_pretrained("Ayushnangia/protovit-deit_small_patch16_224-pins")
+processor = AutoImageProcessor.from_pretrained("Ayushnangia/protovit-deit_small_patch16_224-pins")
+
+# Prepare image
+image = Image.open("path_to_your_image.jpg")
+inputs = processor(images=image, return_tensors="pt")
+
+# Make prediction
+outputs = model(**inputs)
+predicted_label = outputs.logits.argmax(-1).item()
+```
+
+## Additional Information
+
+For more details about the implementation and training process, please visit the [GitHub repository](https://github.com/ayushnangia/ProtoViT).

config.json

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+{
+  "architectures": [
+    "DeiTForImageClassification"
+  ],
+  "model_type": "deit",
+  "num_labels": 155,
+  "image_size": 224,
+  "patch_size": 16
+}

pytorch_model.bin

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