Add model card

README.md

@@ -0,0 +1,35 @@
+
+# Cards Image Classification Model
+
+This model is trained to classify images of cards using a custom dataset.
+
+## Model Details
+
+- Architecture: ResNet18
+- Dataset: Cards Image Dataset-Classification
+- Number of Classes: 53
+- Training Epochs: 25
+- Optimizer: Adam
+- Loss Function: CrossEntropyLoss
+
+## Usage
+
+To use this model, follow the example code below:
+
+```python
+from transformers import AutoModelForImageClassification, AutoFeatureExtractor
+from PIL import Image
+import requests
+
+model_name = "sabrilben/cards_image_classification"
+model = AutoModelForImageClassification.from_pretrained(model_name)
+feature_extractor = AutoFeatureExtractor.from_pretrained(model_name)
+
+url = "path/to/image.jpg"
+image = Image.open(requests.get(url, stream=True).raw)
+inputs = feature_extractor(images=image, return_tensors="pt")
+outputs = model(**inputs)
+logits = outputs.logits
+predicted_class_idx = logits.argmax(-1).item()
+print("Predicted class:", model.config.id2label[predicted_class_idx])```
+