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update README.md

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@@ -30,6 +30,13 @@ This repository provides five pretrained variants — Nano, Small, Medium, Large
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  </div>
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  ## D-FINE Variants
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  The D-FINE family includes five model sizes trained on the [L&A Pucks Dataset](https://huggingface.co/datasets/Laudando-Associates-LLC/pucks), each offering a different balance between model size and detection accuracy.
@@ -72,7 +79,7 @@ model = AutoModel.from_pretrained(f"Laudando-Associates-LLC/d-fine-nano", trust_
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  # Process the image, reize and pad
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  inputs = processor(image)
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- # Run inferece
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  outputs = model(**inputs, conf_threshold=0.4)
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  # Get outputs
 
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  </div>
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+ ## Try it in the Browser
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+ You can test the model using our interactive Gradio demo:
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+ [![Gradio App](https://img.shields.io/badge/Launch%20Demo-Gradio-FF4B4B?logo=gradio&logoColor=white&style=for-the-badge)](https://huggingface.co/spaces/Laudando-Associates-LLC/d-fine-demo)
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  ## D-FINE Variants
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  The D-FINE family includes five model sizes trained on the [L&A Pucks Dataset](https://huggingface.co/datasets/Laudando-Associates-LLC/pucks), each offering a different balance between model size and detection accuracy.
 
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  # Process the image, reize and pad
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  inputs = processor(image)
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+ # Run inference
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  outputs = model(**inputs, conf_threshold=0.4)
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  # Get outputs