Create README.md

README.md

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+---
+license: mit
+language:
+- en
+library_name: transformers
+tags:
+- cv
+- robotics
+---
+# 🌌 Celestial-Mini: Lightweight Object Detection Model (TF)
+
+[![TensorFlow](https://img.shields.io/badge/framework-TensorFlow-orange)](https://www.tensorflow.org/)
+[![Object Detection](https://img.shields.io/badge/task-Object%20Detection-blue)]()
+[![Models](https://img.shields.io/badge/targets-80%20Objects-green)]()
+
+**Celestial-Mini** is a compact, high-performance object detection model designed to recognize up to **80 distinct object classes**. Built with **TensorFlow**, it balances speed and accuracy for deployment in edge devices and real-time applications.
+
+---
+
+## 🚀 Key Features
+
+- 🔍 Detects up to **80 different object categories**
+- ⚡ Optimized for **real-time inference**
+- 🧠 Built on a **lightweight backbone**
+- 📦 TensorFlow SavedModel format for easy deployment
+- 🧰 Compatible with TensorFlow Lite and TensorFlow.js
+
+---
+
+## 🧪 Intended Use
+
+Celestial-Mini is designed for:
+
+- Robotics and drones
+- Smart home devices
+- Augmented Reality (AR) systems
+- Mobile applications
+- Educational and prototyping environments
+
+---
+
+## 🏷 Object Classes
+
+Includes detection support for the standard 80-class COCO-style object categories such as:
+
+```
+person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, ...
+```
+
+---
+
+## 📦 How to Use
+
+```python
+import tensorflow as tf
+
+# Load the model
+model = tf.saved_model.load("path/to/celestial-mini")
+
+# Run inference
+detections = model(input_tensor)
+```
+
+---
+
+## 📊 Performance
+
+| Metric         | Value         |
+|----------------|---------------|
+| Classes        | 80            |
+| Model Size     | ~15MB         |
+| Inference Time | < 50ms/image  |
+| Framework      | TensorFlow    |
+
+> 📌 Performance may vary depending on hardware and TensorFlow backend optimizations.
+
+---
+
+## 🧠 Training & Dataset
+
+Celestial-Mini was trained on a custom variant of the **COCO dataset**, emphasizing generalization and real-time inference. Model architecture includes quantization-friendly layers and depthwise separable convolutions.
+
+---
+
+## 📖 Citation
+
+If you use **Celestial-Mini** in your work, please consider citing:
+
+```
+@misc{celestialmini2025,
+  title={Celestial-Mini: A Lightweight Real-Time Object Detector},
+  author={Lang, John},
+  year={2025},
+  howpublished={\url{https://huggingface.co/langutang/celestial-mini}}
+}
+```
+
+---
+
+## 📬 Contact & License
+
+- 📫 For questions or collaboration, open an issue or contact the maintainer.
+- ⚖️ License: MIT (see LICENSE file for details)
+
+---
+
+## 🌠 Hugging Face Model Hub
+
+To load from Hugging Face:
+
+```python
+from transformers import AutoFeatureExtractor, TFModelForObjectDetection
+
+model = TFModelForObjectDetection.from_pretrained("langutang/celestial-mini")
+extractor = AutoFeatureExtractor.from_pretrained("langutang/celestial-mini")
+```
+
+---
+
+Transform your edge AI projects with the power of **Celestial-Mini** 🌠