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README.md

@@ -16,13 +16,13 @@ npm i @huggingface/transformers
 import { pipeline } from '@huggingface/transformers';
 
 // Create the pipeline
-const pipe = await pipeline('automatic-speech-recognition', 'Xenova/whisper-small.en', {
+const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-small.en', {
     dtype: 'fp32',  // Options: "fp32", "fp16", "q8", "q4"
 });
 
 // Use the model
-const result = await pipe('input text or data');
-console.log(result);
+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`).