Upload README.md with huggingface_hub

README.md

@@ -5,4 +5,23 @@ base_model: ustc-community/dfine_x_obj365
 
 https://huggingface.co/ustc-community/dfine_x_obj365 with ONNX weights to be compatible with Transformers.js.
 
+
+### Transformers.js
+
+If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
+```bash
+npm i @huggingface/transformers
+```
+
+You can then use the model like this:
+```js
+import { pipeline } from "@huggingface/transformers";
+
+const detector = await pipeline("object-detection", "onnx-community/dfine_x_obj365-ONNX");
+
+const image = "https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg";
+const output = await detector(image, { threshold: 0.5 });
+console.log(output);
+```
+
 Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).