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README.md

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+
+---
+license: mit
+tags:
+- image-classification
+- stl10
+- resnet18
+- pytorch
+datasets:
+- Chiranjeev007/STL-10_Subset
+metrics:
+- accuracy
+---
+
+# STL-10 ResNet-18 Classification Model
+
+This model is a fine-tuned ResNet-18 for STL-10 image classification.
+
+## Model Details
+- Base Model: ResNet-18 (pretrained on ImageNet)
+- Dataset: STL-10 Subset
+- Classes: 10
+- Accuracy: 0.8400
+
+## Class Names
+airplane, bird, car, cat, deer, dog, horse, monkey, ship, truck
+
+## Usage
+
+```python
+import torch
+from torchvision import transforms
+from PIL import Image
+
+# Load model (implement loading logic)
+# model = load_model()
+
+# Define transform
+transform = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
+])
+
+# Inference
+image = Image.open("path/to/image.jpg")
+input_tensor = transform(image).unsqueeze(0)
+with torch.no_grad():
+    outputs = model(input_tensor)
+    predicted_class = torch.argmax(outputs, dim=1)
+```