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 (c0082ab89e9a1340db06835c12639f750d35ddfe)
Co-authored-by: Yuichiro Tachibana <[email protected]>
- README.md +16 -0
 - onnx/model.onnx +3 -0
 - onnx/model_bnb4.onnx +3 -0
 - onnx/model_fp16.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 +5,20 @@ library_name: transformers.js 
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            https://huggingface.co/MBZUAI/LaMini-GPT-124M 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 [🤗 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/MBZUAI/LaMini-GPT-124M 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:** Text generation.
         
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            ```js
         
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            import { pipeline } from '@huggingface/transformers';
         
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            const generator = await pipeline('text-generation', 'Xenova/LaMini-GPT-124M');
         
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            const output = await generator('Once upon a time, there was', { max_new_tokens: 10 });
         
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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 [🤗 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.onnx
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        onnx/model_bnb4.onnx
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