metadata
base_model: alchemab/antiberta2
library_name: transformers.js
https://huggingface.co/alchemab/antiberta2 with ONNX weights to be compatible with Transformers.js.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @xenova/transformers
Example: Masked language modelling with Xenova/antiberta2.
import { pipeline } from '@xenova/transformers';
// Create a masked language modelling pipeline
const pipe = await pipeline('fill-mask', 'Xenova/antiberta2');
const output = await pipe('Ḣ Q V Q ... C A [MASK] D ... T V S S');
console.log(output);
// [
// {
// score: 0.48774364590644836,
// token: 19,
// token_str: 'R',
// sequence: 'Ḣ Q V Q C A R D T V S S'
// },
// {
// score: 0.2768442928791046,
// token: 18,
// token_str: 'Q',
// sequence: 'Ḣ Q V Q C A Q D T V S S'
// },
// ...
// ]
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 and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).