๐—˜๐˜…๐˜๐—ฟ๐—ฎ๐—ฐ๐˜๐—ถ๐—ป๐—ด ๐˜†๐—ผ๐˜‚๐—ฟ ๐—›๐—ง๐— ๐—Ÿ ๐˜„๐—ฒ๐—ฏ๐—ฝ๐—ฎ๐—ด๐—ฒ๐˜€ ๏ฟฝ... | ๐—˜๐˜…๐˜๐—ฟ๐—ฎ๐—ฐ๐˜๐—ถ๐—ป๐—ด ๐˜†๐—ผ๐˜‚๐—ฟ ๐—›๐—ง๐— ๐—Ÿ ๐˜„๐—ฒ๐—ฏ๐—ฝ๐—ฎ๐—ด๐—ฒ๐˜€ ๏ฟฝ...
๐—˜๐˜…๐˜๐—ฟ๐—ฎ๐—ฐ๐˜๐—ถ๐—ป๐—ด ๐˜†๐—ผ๐˜‚๐—ฟ ๐—›๐—ง๐— ๐—Ÿ ๐˜„๐—ฒ๐—ฏ๐—ฝ๐—ฎ๐—ด๐—ฒ๐˜€ ๐˜๐—ผ ๐—บ๐—ฎ๐—ฟ๐—ธ๐—ฑ๐—ผ๐˜„๐—ป ๐—ถ๐˜€ ๐—ป๐—ผ๐˜„ ๐—ฝ๐—ผ๐˜€๐˜€๐—ถ๐—ฏ๐—น๐—ฒ ๐—ฒ๐—ป๐—ฑ-๐˜๐—ผ-๐—ฒ๐—ป๐—ฑ ๐˜„๐—ถ๐˜๐—ต ๐—ฎ ๐˜€๐—ถ๐—บ๐—ฝ๐—น๐—ฒ ๐—Ÿ๐—Ÿ๐— ! ๐Ÿ‘

Jina just released Reader-LM, that handles the whole pipeline of extracting markdown from HTML webpages.

A while ago, Jina had released a completely code-based deterministic program to do this extraction, based on some heuristics : e.g., โ€œif the text is in a <p> tag, keep it, but if itโ€™s hidden behind another, remove itโ€.

๐Ÿค” But they received complaints from readers: some found it too detailed, other not enough, depending on the pages.

โžก๏ธ So they decided, ๐—บ๐—ฎ๐˜†๐—ฏ๐—ฒ ๐—ต๐—ฒ๐˜‚๐—ฟ๐—ถ๐˜€๐˜๐—ถ๐—ฐ๐˜€ ๐˜„๐—ฒ๐—ฟ๐—ฒ ๐—ป๐—ผ๐˜ ๐—ฒ๐—ป๐—ผ๐˜‚๐—ด๐—ต: ๐—ถ๐—ป๐˜€๐˜๐—ฒ๐—ฎ๐—ฑ, ๐˜๐—ต๐—ฒ๐˜† ๐˜๐—ฟ๐—ถ๐—ฒ๐—ฑ ๐˜๐—ผ ๐˜๐—ฟ๐—ฎ๐—ถ๐—ป ๐—ฎ ๐—Ÿ๐—Ÿ๐—  ๐˜๐—ผ ๐—ฑ๐—ผ ๐˜๐—ต๐—ฒ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—น๐—ฒ๐˜๐—ฒ ๐—ฒ๐˜…๐˜๐—ฟ๐—ฎ๐—ฐ๐˜๐—ถ๐—ผ๐—ป. This LLM does not need to be very strong,but it should handle a very long context: itโ€™s a challenging, โ€œshallow-but-wideโ€ architecture.

๐—ง๐—ฒ๐—ฐ๐—ต๐—ป๐—ถ๐—ฐ๐—ฎ๐—น ๐—ถ๐—ป๐˜€๐—ถ๐—ด๐—ต๐˜๐˜€:
2๏ธโƒฃ models: Reader-LM-0.5B and 1.5B
โš™๏ธ Two stages of training: first, short and simple HTML to get the basics, then ramp up to longer and harder HTML up to 128k tokens
๐Ÿ”Ž Use contrastive search for decoding: this empirically reduces โ€œrepeating outputโ€ issues
โžก๏ธ Their models beat much larger models at HTML extraction ๐Ÿ”ฅ
๐Ÿค— Weights available on HF (sadly cc-by-nc license):
jinaai/reader-lm-1.5b