Upload README.md

README.md

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+---
+model_name: "Wheat Anomaly Detection Model"
+tags:
+  - pytorch
+  - resnet
+  - agriculture
+  - anomaly-detection
+license: apache-2.0
+library_name: pytorch
+
+# Wheat Anomaly Detection Model
+
+This model is a PyTorch-based ResNet model trained to detect anomalies in wheat crops, such as diseases, pests, and nutrient deficiencies.
+
+## How to Load the Model
+
+To load the trained model, use the following code:
+
+```python
+from transformers import AutoModelForImageClassification
+import torch
+
+# Load the pre-trained model
+model = AutoModelForImageClassification.from_pretrained('your_huggingface_username/your_model_name')
+
+# Put the model in evaluation mode
+model.eval()
+
+# Example of making a prediction
+image_path = "path_to_your_image.jpg"  # Replace with your image path
+image = Image.open(image_path)
+inputs = transform(image).unsqueeze(0)  # Apply the necessary transformations to the image
+inputs = inputs.to(device)
+
+# Make a prediction
+with torch.no_grad():
+    outputs = model(inputs)
+    predicted_class = torch.argmax(outputs.logits, dim=1)
+    print(f"Predicted Class: {predicted_class.item()}")