Update README.md

README.md

@@ -46,27 +46,4 @@ optimising for **Tesla Recall** to minimise missed detections.
 | Precision (Tesla)   | 93.3%  |
 | Recall (Tesla)      | 97.0%  |
 | F1 Score (Tesla)    | 95.1%  |
-| F1 Score (Not Tesla)| 94.9%  |
-
-## Usage
-
-```python
-from transformers import AutoImageProcessor, AutoModelForImageClassification
-from PIL import Image
-import torch
-
-model = AutoModelForImageClassification.from_pretrained("YOUR_USERNAME/YOUR_MODEL_NAME")
-processor = AutoImageProcessor.from_pretrained("YOUR_USERNAME/YOUR_MODEL_NAME")
-
-image = Image.open("car.jpg").convert("RGB")
-inputs = processor(images=image, return_tensors="pt")
-
-with torch.no_grad():
-    outputs = model(**inputs)
-
-probs = torch.nn.functional.softmax(outputs.logits, dim=-1)
-tesla_prob = probs.item()  # index 1 = tesla[1]
-
-THRESHOLD = 0.6
-print("Is Tesla?", "YES ✅" if tesla_prob >= THRESHOLD else "NO ❌")
-print(f"Tesla probability: {tesla_prob:.3f}")
+| F1 Score (Not Tesla)| 94.9%  |