Add/update the quantized ONNX model files and README.md for Transformers.js v3

#1
by whitphx - opened
README.md CHANGED
@@ -8,4 +8,21 @@ tags:
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  https://huggingface.co/microsoft/dit-large with ONNX weights to be compatible with Transformers.js.
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  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 [πŸ€— Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
 
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  https://huggingface.co/microsoft/dit-large with ONNX weights to be compatible with Transformers.js.
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+ ## Usage (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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+
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+ **Example:** Perform image feature extraction.
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+
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+ ```js
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+ import { pipeline } from '@huggingface/transformers';
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+
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+ const image_feature_extractor = await pipeline('image-feature-extraction', 'Xenova/dit-large');
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+ const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png';
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+ const features = await image_feature_extractor(url);
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+ ```
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+
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  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 [πŸ€— Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
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