Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#1)

- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (6eee87fd268b35dfcab0059b467e5ece3f73d708)


Co-authored-by: Yuichiro Tachibana <[email protected]>

README.md

@@ -6,22 +6,21 @@ pipeline_tag: object-detection
 
 https://github.com/WongKinYiu/yolov9 with ONNX weights to be compatible with Transformers.js.
 
-
 ## Usage (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/@xenova/transformers) using:
+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 @xenova/transformers
+npm i @huggingface/transformers
 ```
 
 **Example:** Perform object-detection with `Xenova/yolov9-c_all`.
 
 ```js
-import { AutoModel, AutoProcessor, RawImage } from '@xenova/transformers';
+import { AutoModel, AutoProcessor, RawImage } from '@huggingface/transformers';
 
 // Load model
 const model = await AutoModel.from_pretrained('Xenova/yolov9-c_all', {
-    // quantized: false,    // (Optional) Use unquantized version.
+    dtype: "fp32",    // (Optional) Use unquantized version.
 })
 
 // Load processor
@@ -62,5 +61,4 @@ Test it out [here](https://huggingface.co/spaces/Xenova/video-object-detection)!
 
 ---
 
-
 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`).