Add/update the quantized ONNX model files and README.md for Transformers.js v3
#1
by
whitphx
HF Staff
- opened
- README.md +4 -5
- 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
CHANGED
|
@@ -7,18 +7,18 @@ https://huggingface.co/YituTech/conv-bert-medium-small with ONNX weights to be c
|
|
| 7 |
|
| 8 |
## Usage (Transformers.js)
|
| 9 |
|
| 10 |
-
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/@
|
| 11 |
```bash
|
| 12 |
-
npm i @
|
| 13 |
```
|
| 14 |
|
| 15 |
**Example:** Feature extraction w/ `Xenova/conv-bert-medium-small`.
|
| 16 |
|
| 17 |
```javascript
|
| 18 |
-
import { pipeline } from '@
|
| 19 |
|
| 20 |
// Create feature extraction pipeline
|
| 21 |
-
const extractor = await pipeline('feature-extraction', 'Xenova/conv-bert-medium-small', {
|
| 22 |
|
| 23 |
// Perform feature extraction
|
| 24 |
const output = await extractor('This is a test sentence.');
|
|
@@ -33,5 +33,4 @@ console.log(output)
|
|
| 33 |
|
| 34 |
---
|
| 35 |
|
| 36 |
-
|
| 37 |
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 [π€ Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
|
|
|
|
| 7 |
|
| 8 |
## Usage (Transformers.js)
|
| 9 |
|
| 10 |
+
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:
|
| 11 |
```bash
|
| 12 |
+
npm i @huggingface/transformers
|
| 13 |
```
|
| 14 |
|
| 15 |
**Example:** Feature extraction w/ `Xenova/conv-bert-medium-small`.
|
| 16 |
|
| 17 |
```javascript
|
| 18 |
+
import { pipeline } from '@huggingface/transformers';
|
| 19 |
|
| 20 |
// Create feature extraction pipeline
|
| 21 |
+
const extractor = await pipeline('feature-extraction', 'Xenova/conv-bert-medium-small', { dtype: "fp32" }); // Options: "fp32", "fp16", "q8", "q4"
|
| 22 |
|
| 23 |
// Perform feature extraction
|
| 24 |
const output = await extractor('This is a test sentence.');
|
|
|
|
| 33 |
|
| 34 |
---
|
| 35 |
|
|
|
|
| 36 |
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 [π€ 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
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cb57c2671181d94853945e3fedc5f7c94463bfa6e55b9a3b6b2e225f37d90582
|
| 3 |
+
size 51698508
|
onnx/model_q4.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7563188c0022a199b3fbf16a7c35ad53c841929c31a58ab735b4965af87e3222
|
| 3 |
+
size 52037992
|
onnx/model_q4f16.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f9db79bba23b0065948cfd0deba80fe8aa8bf2491583eca018f2732480836127
|
| 3 |
+
size 27627345
|
onnx/model_uint8.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:26ad7dac3319744ee6969182d0b5090dfd10543615f6342d999ad042a09eb9e4
|
| 3 |
+
size 18302304
|