2.13.4

What's new?

• Add support for cross-encoder models (+fix token type ids) (#501)

  Example: Information Retrieval w/ Xenova/ms-marco-TinyBERT-L-2-v2.

  import { AutoTokenizer, AutoModelForSequenceClassification } from '@xenova/transformers';
  
  const model = await AutoModelForSequenceClassification.from_pretrained('Xenova/ms-marco-TinyBERT-L-2-v2');
  const tokenizer = await AutoTokenizer.from_pretrained('Xenova/ms-marco-TinyBERT-L-2-v2');
  
  const features = tokenizer(
      ['How many people live in Berlin?', 'How many people live in Berlin?'],
      {
          text_pair: [
              'Berlin has a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.',
              'New York City is famous for the Metropolitan Museum of Art.',
          ],
          padding: true,
          truncation: true,
      }
  )
  
  const { logits } = await model(features)
  console.log(logits.data);
  // quantized:   [ 7.210887908935547, -11.559350967407227 ]
  // unquantized: [ 7.235750675201416, -11.562294006347656 ]

  Check out the list of pre-converted models here. We also put out a demo for you to try out.

Full Changelog: 2.13.3...2.13.4