/* 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" }); | |
}); |