Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#1)

- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (4205b8a9c6fdec5cfe8aff7702959625bed67e87)


Co-authored-by: Yuichiro Tachibana <[email protected]>

README.md

@@ -7,15 +7,15 @@ https://huggingface.co/BAAI/bge-large-en-v1.5 with ONNX weights to be compatible
 
 ## Usage (Transformers.js)
 
-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/@xenova/transformers) using:
+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:
 ```bash
-npm i @xenova/transformers
+npm i @huggingface/transformers
 ```
 
 You can then use the model to compute embeddings, as follows:
 
 ```js
-import { pipeline } from '@xenova/transformers';
+import { pipeline } from '@huggingface/transformers';
 
 // Create a feature-extraction pipeline
 const extractor = await pipeline('feature-extraction', 'Xenova/bge-large-en-v1.5');
@@ -40,7 +40,7 @@ console.log(embeddings.tolist()); // Convert embeddings to a JavaScript list
 
 You can also use the model for retrieval. For example:
 ```js
-import { pipeline, cos_sim } from '@xenova/transformers';
+import { pipeline, cos_sim } from '@huggingface/transformers';
 
 // Create a feature-extraction pipeline
 const extractor = await pipeline('feature-extraction', 'Xenova/bge-large-en-v1.5');
@@ -76,5 +76,4 @@ console.log(scores);
 // ]
 ```
 
-
 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`).

onnx/model_bnb4.onnx

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onnx/model_int8.onnx

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onnx/model_q4.onnx

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onnx/model_q4f16.onnx

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onnx/model_uint8.onnx

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