Update README.md

README.md

@@ -48,29 +48,5 @@ For detailed performance metrics including precision, recall, and F1-score per c
 
 ## Usage
 
-### With Transformers Pipeline
-```python
-from transformers import pipeline
-
-classifier = pipeline("image-classification", model="keanteng/efficientnet-b7-breast-cancer-classification-0603-3")
-result = classifier("path/to/mammogram.jpg")
-print(result)
-```
-
-```python
-from transformers import AutoFeatureExtractor, AutoModelForImageClassification
-from PIL import Image
-
-# Load model and feature extractor
-model = AutoModelForImageClassification.from_pretrained("keanteng/efficientnet-b7-breast-cancer-classification-0603-3")
-feature_extractor = AutoFeatureExtractor.from_pretrained("keanteng/efficientnet-b7-breast-cancer-classification-0603-3")
-# Prepare image
-image = Image.open("path/to/mammogram.jpg").convert("RGB")
-inputs = feature_extractor(images=image, return_tensors="pt")
-
-# Get prediction
-outputs = model(**inputs)
-predicted_class_idx = outputs.logits.argmax(-1).item()
-print(f"Predicted class: model.config.id2label[predicted_class_idx]")
-```
+Please check the [inference compute](https://github.com/keanteng/wqd7025/blob/main/inference/inference_comparison.ipynb).