update README.md

README.md

@@ -54,6 +54,79 @@ model-index:
 
 <h1 align="center"><strong>D-FINE Small</strong></h1>
 
+<p align="center">
+  <a href="https://huggingface.co/Laudando-Associates-LLC/d-fine-small">
+    <img src="https://img.shields.io/badge/HuggingFace-Model-yellow?logo=huggingface&style=for-the-badge">
+  </a>
+</p>
+
+This repository contains the [D-FINE](https://arxiv.org/abs/2410.13842) Small model, a real-time object detector designed for efficient and accurate object detection tasks.
+
+## Try it in the Browser
+
+You can test this model using our interactive Gradio demo:
+
+<p align="center">
+  <a href="https://huggingface.co/spaces/Laudando-Associates-LLC/d-fine-demo">
+    <img src="https://img.shields.io/badge/Launch%20Demo-Gradio-FF4B4B?logo=gradio&logoColor=white&style=for-the-badge">
+  </a>
+</p>
+
+## Model Overview
+
+* Architecture: D-FINE Small
+
+* Parameters: 10.3M
+
+* Performance: 
+  
+  - mAP@[0.50:0.95]: 0.816
+
+  - mAP@[0.50]: 0.983
+
+  - AR@[0.50:0.95]: 0.859
+
+  - F1 Score: 0.951
+
+* Framework: PyTorch / ONNX
+
+* Training Hardware: 2× NVIDIA RTX A6000 GPUs
+
+## Download
+
+| Format | Link |
+|:--------:|:------:|
+| ONNX   | <a href="https://huggingface.co/Laudando-Associates-LLC/d-fine-small/resolve/main/model.onnx"><img src="https://img.shields.io/badge/-ONNX-005CED?style=for-the-badge&logo=onnx&logoColor=white"></a> |
+| PyTorch | <a href="https://huggingface.co/Laudando-Associates-LLC/d-fine-small/resolve/main/pytorch_model.bin"><img src="https://img.shields.io/badge/PyTorch-EE4C2C?style=for-the-badge&logo=pytorch&logoColor=white"></a> |
+
+## Usage
+
+To utilize this model, ensure you have the shared [D-FINE processor](https://huggingface.co/Laudando-Associates-LLC/d-fine):
+
+```python
+from transformers import AutoProcessor, AutoModel
+
+# Load processor
+processor = AutoProcessor.from_pretrained("Laudando-Associates-LLC/d-fine", trust_remote_code=True)
+
+# Load model
+model = AutoModel.from_pretrained("Laudando-Associates-LLC/d-fine-small", trust_remote_code=True)
+
+# Process image
+inputs = processor(image)
+
+# Run inference
+outputs = model(**inputs, conf_threshold=0.4)
+```
+
+## Evaluation
+
+This model was trained and evaluated on the [L&A Pucks Dataset](https://huggingface.co/datasets/Laudando-Associates-LLC/pucks).
+
+## License
+
+This model is licensed under the [Apache License 2.0](https://github.com/Peterande/D-FINE/blob/master/LICENSE).
+
 ## Citation
 If you use `D-FINE` or its methods in your work, please cite the following BibTeX entries: