Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#1)
Browse files- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (3f3e772b5dcbe464c764bf39b64b8b5e6ad8a198)
Co-authored-by: Yuichiro Tachibana <[email protected]>
- README.md +18 -0
- onnx/model_bnb4.onnx +3 -0
- onnx/model_int8.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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@@ -5,4 +5,22 @@ library_name: transformers.js
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https://huggingface.co/hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering 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 [馃 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/hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering with ONNX weights to be compatible with Transformers.js.
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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:** Run question answering.
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```js
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import { pipeline } from '@huggingface/transformers';
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const answerer = await pipeline('question-answering', 'Xenova/tiny-random-RoFormerForQuestionAnswering');
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const question = 'Who was Jim Henson?';
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const context = 'Jim Henson was a nice puppet.';
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const output = await answerer(question, context);
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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 [馃 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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onnx/model_bnb4.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:01c394f0147511c6a1d60d767535a07f2b298be93c7d52b7db15832c57eb2075
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size 6600601
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onnx/model_int8.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:a6a99dfffc0eabf4f1e0c77e3328fbb241ff6ac2a8db7bc992c1227a6f417ea8
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size 1838183
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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 sha256:91dd4b466374043d81106086b4603ced89b170826d3e495407165fc9d86da8d2
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size 6605118
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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 sha256:345876bd4abe2db0e126235f575aeb4c84232423e93016829f8481cb92a10513
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size 3393787
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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 sha256:5b692265aa5f8e9634a97d9dd8cba74e4b9e80906cb6624dc8bd85a26fcf435c
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size 1838196
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