Function WithXLMRoBERTa

Example

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

import { AutoTokenizer } from "@huggingface/transformers";

const modelName = "atjsh/llmlingua-2-js-xlm-roberta-large-meetingbank";
const oai_tokenizer = await AutoTokenizer.from_pretrained("Xenova/gpt-4o");

const { promptCompressor } = await LLMLingua2.WithXLMRoBERTa(modelName,
 {
   transformersJSConfig: {
     device: "auto",
     dtype: "fp32",
   },
   oaiTokenizer: oai_tokenizer,
   modelOptions: {
     use_external_data_format: true,
   },
 }
);

const compressedText: string = await promptCompressor.compress(
 "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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