Add/update the quantized ONNX model files and README.md for Transformers.js v3
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README.md
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# text-embedding-ada-002 Tokenizer
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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/
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##
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```
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tokenizer = GPT2TokenizerFast.from_pretrained('Xenova/text-embedding-ada-002')
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assert tokenizer.encode('hello world') == [15339, 1917]
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```
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```js
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import { AutoTokenizer } from '@
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const tokenizer = await AutoTokenizer.from_pretrained('Xenova/text-embedding-ada-002');
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const tokens = tokenizer.encode('hello world'); // [15339, 1917]
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```
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# text-embedding-ada-002 Tokenizer
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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).
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## Usage (Transformers.js)
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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:
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```bash
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npm i @huggingface/transformers
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```
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**Example:** Tokenizer usage with Transformers.js
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```js
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import { AutoTokenizer } from '@huggingface/transformers';
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const tokenizer = await AutoTokenizer.from_pretrained('Xenova/text-embedding-ada-002');
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const tokens = tokenizer.encode('hello world'); // [15339, 1917]
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```
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### Transformers/Tokenizers
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```py
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from transformers import GPT2TokenizerFast
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tokenizer = GPT2TokenizerFast.from_pretrained('Xenova/text-embedding-ada-002')
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assert tokenizer.encode('hello world') == [15339, 1917]
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```
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