Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#2)

- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (82873170d9e4b76ccd9a5c2ac0c3b428879f72e9)


Co-authored-by: Yuichiro Tachibana <whitphx@users.noreply.huggingface.co>

README.md

@@ -18,19 +18,19 @@ https://huggingface.co/jinaai/jina-embeddings-v2-base-de with ONNX weights to be
 
 ## 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, cos_sim } from '@xenova/transformers';
+import { pipeline, cos_sim } from '@huggingface/transformers';
 
 // Create a feature extraction pipeline
 const extractor = await pipeline('feature-extraction', 'Xenova/jina-embeddings-v2-base-de', {
-    quantized: false, // Comment out this line to use the quantized version
+    dtype: "fp32"  // Options: "fp32", "fp16", "q8", "q4"
 });
 
 // Compute sentence embeddings
@@ -51,4 +51,4 @@ console.log(score);
 
 ---
 
-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`).
+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

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8ab7347d77642646bbff73027b7d294806a73d67e93d81d739ea5808c74aa2d
+size 251953322

onnx/model_int8.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:89d0966581ca4c4fae3ec21e23bc387637e0f053a131f0322dac568527eb00ad
+size 160893546

onnx/model_q4.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6a7e897f75576b09a2245c04070b816a917f74da6818ad1e9443970d1240010
+size 259030670

onnx/model_q4f16.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d06c3d3a791cf1bba67fa8b4bbe205759dcf38e241c0110caf8058cbd9ee0f6
+size 157999063

onnx/model_uint8.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6966e78f28c22c71d4bec84a9e8b3310d1684400eb3e98fb85d465d53cd3c5ae
+size 160893583