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

README.md

@@ -7,9 +7,9 @@ tags:
 
 # text-embedding-ada-002 Tokenizer
 
-A 🤗-compatible version of the **text-embedding-ada-002 tokenizer** (adapted from [openai/tiktoken](https://github.com/openai/tiktoken)). This means it can be used with Hugging Face libraries including [Transformers](https://github.com/huggingface/transformers), [Tokenizers](https://github.com/huggingface/tokenizers), and [Transformers.js](https://github.com/xenova/transformers.js).
+A 🤗-compatible version of the **text-embedding-ada-002 tokenizer** (adapted from [openai/tiktoken](https://github.com/openai/tiktoken)). This means it can be used with Hugging Face libraries including [Transformers](https://github.com/huggingface/transformers), [Tokenizers](https://github.com/huggingface/tokenizers), and [Transformers.js](https://github.com/huggingface/transformers.js).
 
-## Example usage:
+## Usage
 
 ### Transformers/Tokenizers
 ```py
@@ -20,8 +20,13 @@ assert tokenizer.encode('hello world') == [15339, 1917]
 ```
 
 ### 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
+```
+
 ```js
-import { AutoTokenizer } from '@xenova/transformers';
+import { AutoTokenizer } from '@huggingface/transformers';
 
 const tokenizer = await AutoTokenizer.from_pretrained('Xenova/text-embedding-ada-002');
 const tokens = tokenizer.encode('hello world'); // [15339, 1917]