Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#2)
Browse files- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (55f36f98225bd0f2758864c12e9238471cf00637)
Co-authored-by: Yuichiro Tachibana <whitphx@users.noreply.huggingface.co>
- README.md +3 -3
- onnx/model_bnb4.onnx +3 -0
- onnx/model_q4.onnx +3 -0
- onnx/model_q4f16.onnx +3 -0
- onnx/model_uint8.onnx +3 -0
README.md
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@@ -7,14 +7,14 @@ https://huggingface.co/apple/mobilevit-small with ONNX weights to be compatible
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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/@
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```bash
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npm i @
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```
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**Example:** Perform image classification with `Xenova/mobilevit-small`
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```js
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import { pipeline } from '@
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// Create an image classification pipeline
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const classifier = await pipeline('image-classification', 'Xenova/mobilevit-small', {
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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:** Perform image classification with `Xenova/mobilevit-small`
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```js
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import { pipeline } from '@huggingface/transformers';
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// Create an image classification pipeline
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const classifier = await pipeline('image-classification', 'Xenova/mobilevit-small', {
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onnx/model_bnb4.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:bc9c02e0948cc104ae65c664254c5d1d703a0d93097d41223788a2ad50776022
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size 12592898
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onnx/model_q4.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:a76335d22418911ed1c16d2adb255866e4d7079ce8d8e10be1a42f8e8eac28fe
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size 12833818
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onnx/model_q4f16.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:b16a4df0e2454d05379941691f8c546c7f22821c7fea35f6bee097c5cd6f3f2f
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size 7289715
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onnx/model_uint8.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:363865a989b563df81f63188db8f207ca6af054b1f207602d5ecc831c31805d4
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size 6063282
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