metadata
base_model: pythainlp/thainer-corpus-v2-base-model
library_name: transformers.js
https://huggingface.co/pythainlp/thainer-corpus-v2-base-model 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 @huggingface/transformers
Example: Perform named entity recognition.
import { pipeline } from '@huggingface/transformers';
const classifier = await pipeline('token-classification', 'Xenova/thainer-corpus-v2-base-model');
const output = await classifier('My name is Sarah and I live in London');
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).