| 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](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using: | |
| ```bash | |
| npm i @xenova/transformers | |
| ``` | |
| **Example:** Masked language modelling with `Xenova/antiberta2`. | |
| ```js | |
| 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](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`). |