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README.md

@@ -10,17 +10,12 @@ If you haven't already, you can install the [Transformers.js](https://huggingfac
 npm i @huggingface/transformers
 ```
 
+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`).
+
 ```js
 import { pipeline } from '@huggingface/transformers';
 
-// Create the pipeline
-const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-small.en', {
-    dtype: 'fp32',  // Options: "fp32", "fp16", "q8", "q4"
-});
-
-// Use the model
+const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-small.en');
 const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
 const output = await transcriber(url);
-```
-
-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`).
+```