Update README.md

README.md

@@ -9,26 +9,25 @@ tags:
 
 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).
 
-## Usage (Transformers.js)
+## Usage
 
+### Transformers/Tokenizers
+```py
+from transformers import GPT2TokenizerFast
+
+tokenizer = GPT2TokenizerFast.from_pretrained('Xenova/text-embedding-ada-002')
+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
 ```
 
-**Example:** Tokenizer usage with Transformers.js
-
 ```js
 import { AutoTokenizer } from '@huggingface/transformers';
 
 const tokenizer = await AutoTokenizer.from_pretrained('Xenova/text-embedding-ada-002');
 const tokens = tokenizer.encode('hello world'); // [15339, 1917]
 ```
-
-### Transformers/Tokenizers
-```py
-from transformers import GPT2TokenizerFast
-
-tokenizer = GPT2TokenizerFast.from_pretrained('Xenova/text-embedding-ada-002')
-assert tokenizer.encode('hello world') == [15339, 1917]
-```