Update README.md

README.md

@@ -1,29 +1,42 @@
 ---
 license: mit
-tags:
-  - object-detection
-  - yolo
-  - ultralytics
-language: en
-library_name: ultralytics
+datasets:
+- coco
+language: []
+metrics:
+- precision
+- recall
+- mAP50
+- mAP50-95
+base_model: ultralytics/yolov11
 pipeline_tag: object-detection
+library_name: ultralytics
+tags:
+- yolo
+- object-detection
+- computer-vision
+- ultralytics
 ---
 
-# best-p
+# YOLOv11 Object Detection Model
+
+This is a YOLOv11 model trained for object detection tasks. The model was trained using the Ultralytics YOLOv11 framework.
 
-This is a custom YOLOv8 model trained for object detection using Ultralytics.
+## 📦 Model Details
 
-## Example
+- **Framework**: Ultralytics YOLOv11
+- **Task**: Object Detection
+- **Dataset**: COCO format
+- **Model Size**: ~5MB
+- **Author**: [Phurin1](https://huggingface.co/Phurin1)
 
-You can try the hosted inference API or use it locally with `ultralytics`.
+## 🧠 Use with Ultralytics
 
-## How to use
+To use this model in your Python code:
 
 ```python
-from huggingface_hub import hf_hub_download
 from ultralytics import YOLO
 
-model_path = hf_hub_download(repo_id="Phurin1/best-p", filename="best.pt")
-model = YOLO(model_path)
-results = model("your_image.jpg")
+model = YOLO("Phurin1/best-p")  # Or the full URL: "https://huggingface.co/Phurin1/best-p"
+results = model("https://ultralytics.com/images/bus.jpg", save=True)
 results.show()