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

README.md

@@ -7,15 +7,15 @@ https://huggingface.co/YituTech/conv-bert-base with ONNX weights to be compatibl
 
 ## 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:** Feature extraction w/ `Xenova/conv-bert-base`.
 
 ```javascript
-import { pipeline } from '@xenova/transformers';
+import { pipeline } from '@huggingface/transformers';
 
 // Create feature extraction pipeline
 const extractor = await pipeline('feature-extraction', 'Xenova/conv-bert-base');
@@ -33,5 +33,4 @@ 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`).

onnx/model_bnb4.onnx

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onnx/model_q4.onnx

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onnx/model_q4f16.onnx

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onnx/model_uint8.onnx

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