Bump @xenova/transformers from 2.16.1 to 2.17.1

[dependabot[bot]]

Bumps @xenova/transformers from 2.16.1 to 2.17.1.

Release notes

Sourced from @​xenova/transformers's releases.

2.17.1

What's new?

• Add ignore_merges option to BPE tokenizers in xenova/transformers.js#716

Full Changelog: https://github.com/xenova/transformers.js/compare/2.17.0...2.17.1

2.17.0

What's new?

💬 Improved text-generation pipeline for conversational models

This version adds support for passing an array of chat messages (with "role" and "content" properties) to the text-generation pipeline (PR). Check out the list of supported models here.

Example: Chat with Xenova/Qwen1.5-0.5B-Chat.

import { pipeline } from '@xenova/transformers';
// Create text-generation pipeline
const generator = await pipeline('text-generation', 'Xenova/Qwen1.5-0.5B-Chat');
// Define the list of messages
const messages = [
{ role: 'system', content: 'You are a helpful assistant.' },
{ role: 'user', content: 'Tell me a funny joke.' }
]
// Generate text
const output = await generator(messages, {
max_new_tokens: 128,
do_sample: false,
})
console.log(output[0].generated_text);
// [
//   { role: 'system', content: 'You are a helpful assistant.' },
//   { role: 'user', content: 'Tell me a funny joke.' },
//   { role: 'assistant', content: "Sure, here's one:\n\nWhy was the math book sad?\n\nBecause it had too many problems.\n\nI hope you found that joke amusing! Do you have any other questions or topics you'd like to discuss?" },
// ]

We also added the return_full_text parameter, which means if you set return_full_text=false, only the newly-generated tokens will be returned (only applicable if passing the raw text prompt to the pipeline).

🔢 Binary embedding quantization support

Transformers.js v2.17 adds two new parameters to the feature-extraction pipeline ("quantize" and "precision"), enabling you to generate binary embeddings. These can be used with certain embedding models to shrink the size of the document embeddings for retrieval. This results in reductions in index size/memory usage (for storage) and improvements in retrieval speed. Surprisingly, you can still achieve up to ~95% of the original performance, but at 32x storage savings and up to 32x retrieval speeds! 🤯 Thanks to @​jonathanpv for this addition in xenova/transformers.js#691!

import { pipeline } from '@xenova/transformers';
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Commits

• 992f643 [version] Update to 2.17.1
• 6d5901e Add ignore_merges option to BPE tokenizers (#716)
• 6427431 [version] Update to 2.17.0
• c2c45cb Improve support of conversational models (#658)
• aa542cf Update dependencies (#704)
• 15b90b7 maths: switch dot to faster for loop (#667)
• cdbc532 Update dependencies (#702)
• f71ee32 Add binary embedding quantization support to FeatureExtraction pipeline (#691)
• 8804c36 Bump ip from 2.0.0 to 2.0.1 in /examples/electron (#665)
• 3509fc4 Bump webpack-dev-middleware from 5.3.3 to 5.3.4 (#661)
• See full diff in compare view

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