Function WithBERTMultilingual

Example

import { LLMLingua2 } from "@atjsh/llmlingua-2";

import { Tiktoken } from "js-tiktoken/lite";
import o200k_base from "js-tiktoken/ranks/o200k_base";

const modelName = "Arcoldd/llmlingua4j-bert-base-onnx";
const oai_tokenizer = new Tiktoken(o200k_base);

const { promptCompressor } = await LLMLingua2.WithBERTMultilingual(modelName,
 {
   transformerJSConfig: {
     device: "auto",
     dtype: "fp32",
   },
   oaiTokenizer: oai_tokenizer,
   modelSpecificOptions: {
     subfolder: "",
   },
 }
);

const compressedText: string = await promptCompressor.compress_prompt(
 "LLMLingua-2, a small-size yet powerful prompt compression method trained via data distillation from GPT-4 for token classification with a BERT-level encoder, excels in task-agnostic compression. It surpasses LLMLingua in handling out-of-domain data, offering 3x-6x faster performance.",
 { rate: 0.8 }
);

console.log({ compressedText });
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