Xenova HF Staff whitphx HF Staff commited on
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Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#1)

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- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (67cfbece1284f36180b42f67e8dac365a02ff257)


Co-authored-by: Yuichiro Tachibana <[email protected]>

README.md CHANGED
@@ -7,15 +7,15 @@ https://huggingface.co/facebook/dinov2-base-imagenet1k-1-layer with ONNX weights
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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/@xenova/transformers) using:
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  ```bash
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- npm i @xenova/transformers
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  ```
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  **Example:** Image classification w/ `Xenova/dinov2-base-imagenet1k-1-layer`.
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  ```javascript
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- import { pipeline } from '@xenova/transformers';
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  // Create image classification pipeline
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  const classifier = await pipeline('image-classification', 'Xenova/dinov2-base-imagenet1k-1-layer', { quantized: false });
@@ -23,7 +23,7 @@ const classifier = await pipeline('image-classification', 'Xenova/dinov2-base-im
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  // Classify an image
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  const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
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  const output = await classifier(url);
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- console.log(output)
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  // [{ label: 'tabby, tabby cat', score: 0.4475940465927124 }]
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  ```
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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:** Image classification w/ `Xenova/dinov2-base-imagenet1k-1-layer`.
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  ```javascript
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+ import { pipeline } from '@huggingface/transformers';
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  // Create image classification pipeline
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  const classifier = await pipeline('image-classification', 'Xenova/dinov2-base-imagenet1k-1-layer', { quantized: false });
 
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  // Classify an image
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  const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
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  const output = await classifier(url);
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+ console.log(output);
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  // [{ label: 'tabby, tabby cat', score: 0.4475940465927124 }]
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  ```
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