Update README.md
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README.md
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@@ -17,7 +17,7 @@ import { AutoProcessor, VitMatteForImageMatting, RawImage } from '@xenova/transf
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// Load processor and model
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const processor = await AutoProcessor.from_pretrained('Xenova/vitmatte-small-distinctions-646');
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const model = await VitMatteForImageMatting.from_pretrained('Xenova/vitmatte-small-distinctions-646');
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// Load image and trimap
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const image = await RawImage.fromURL('https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/vitmatte_image.png');
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@@ -68,10 +68,9 @@ Example inputs:
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|  |  |
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Example
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|  |  |
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---
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// Load processor and model
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const processor = await AutoProcessor.from_pretrained('Xenova/vitmatte-small-distinctions-646');
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const model = await VitMatteForImageMatting.from_pretrained('Xenova/vitmatte-small-distinctions-646', { quantized: false });
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// Load image and trimap
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const image = await RawImage.fromURL('https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/vitmatte_image.png');
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|--------|--------|
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|  |  |
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Example output:
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
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---
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