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README.md

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+---
+license: apache-2.0
+tags:
+  - image-classification
+  - pytorch
+  - cifar10
+datasets:
+  - uoft-cs/cifar10
+---
+
+# CIFAR-10 CNN Classifier
+
+A 3-block CNN trained from scratch on CIFAR-10 using PyTorch.
+
+## Classes
+plane, car, bird, cat, deer, dog, frog, horse, ship, truck
+
+## Training
+- Architecture: 3× Conv blocks (32→64→128 channels) + FC classifier
+- Optimizer: Adam + OneCycleLR scheduler
+- Augmentation: RandomCrop, RandomFlip, ColorJitter, RandomErasing
+- Validation accuracy: ~80%+ (after 64 epochs)
+
+## Usage
+
+```python
+from transformers import pipeline
+from PIL import Image
+
+classifier = pipeline(
+    "image-classification",
+    model="MarkivDunhar/cifar-cnn"
+)
+
+result = classifier("your_image.jpg")
+print(result)
+# [{'label': 'dog', 'score': 0.91}]
+```

config.json

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+{
+  "architectures": [
+    "CifarCNNModel"
+  ],
+  "dtype": "float32",
+  "id2label": {
+    "0": "plane",
+    "1": "car",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "bird": 2,
+    "car": 1,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "plane": 0,
+    "ship": 8,
+    "truck": 9
+  },
+  "model_type": "cifar-cnn",
+  "num_classes": 10,
+  "transformers_version": "5.12.1"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6c84dcd8c99730aa04486361b277371e7a009b88dacb2e35bdae660ebcef0a06
+size 5375856