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README.md

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+# ResNet50 ImageNet Classifier
+
+## Model Description
+This model is a ResNet50 architecture trained on ImageNet dataset.
+
+## Performance
+- Best Validation Accuracy: 0.00%
+- Training Epochs: 42
+
+## Training Details
+- Framework: PyTorch
+- Task: Image Classification
+- Dataset: ImageNet
+- Input Size: 224x224
+- Number of Classes: 1000
+
+## Usage
+```python
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+import torch
+
+# Load model and processor
+model = AutoModelForImageClassification.from_pretrained("jatingocodeo/ImageNet")
+processor = AutoImageProcessor.from_pretrained("jatingocodeo/ImageNet")
+
+# Prepare image
+image = Image.open("path/to/image.jpg")
+inputs = processor(image, return_tensors="pt")
+
+# Get predictions
+with torch.no_grad():
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class = logits.argmax(-1).item()
+```