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Upload README.md with huggingface_hub

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@@ -3,22 +3,17 @@ base_model: openai/whisper-tiny
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  library_name: transformers.js
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  ---
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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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- https://huggingface.co/openai/whisper-tiny with ONNX weights to be compatible with Transformers.js.
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-
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  ```js
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  import { pipeline } from '@huggingface/transformers';
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- // Create the pipeline
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- const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny', {
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- dtype: 'fp32', // Options: "fp32", "fp16", "q8", "q4"
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- });
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-
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- // Use the model
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  const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
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  const output = await transcriber(url);
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  ```
 
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  library_name: transformers.js
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  ---
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+ https://huggingface.co/openai/whisper-tiny with ONNX weights to be compatible with Transformers.js.
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+
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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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  ```js
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  import { pipeline } from '@huggingface/transformers';
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+ const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny');
 
 
 
 
 
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  const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
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  const output = await transcriber(url);
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  ```