/* eslint-disable no-restricted-globals */ | |
import { pipeline } from '@huggingface/transformers'; | |
class MyZeroShotClassificationPipeline { | |
static task = 'zero-shot-classification'; | |
static model = 'MoritzLaurer/deberta-v3-xsmall-zeroshot-v1.1-all-33'; | |
static instance = null; | |
static async getInstance(progress_callback = null) { | |
this.instance ??= pipeline(this.task, this.model, { | |
progress_callback | |
}); | |
return this.instance; | |
} | |
} | |
// Listen for messages from the main thread | |
self.addEventListener('message', async (event) => { | |
// Retrieve the pipeline. When called for the first time, | |
// this will load the pipeline and save it for future use. | |
const classifier = await MyZeroShotClassificationPipeline.getInstance((x) => { | |
// We also add a progress callback to the pipeline so that we can | |
// track model loading. | |
self.postMessage({ status: 'progress', output: x }); | |
}); | |
const { text, labels } = event.data; | |
const split = text.split('\n'); | |
for (const line of split) { | |
const output = await classifier(line, labels, { | |
hypothesis_template: 'This text is about {}.', | |
multi_label: true | |
}); | |
// Send the output back to the main thread | |
self.postMessage({ status: 'output', output }); | |
} | |
// Send the output back to the main thread | |
self.postMessage({ status: 'complete' }); | |
}); | |