๊ฐ€์ž… ํ›„ ์ดˆ๋Œ€ ๋งํฌ๋ฅผ ๊ณต์œ ํ•˜๋ฉด ๋™์˜์ƒ ์žฌ์ƒ ๋ฐ ์ดˆ๋Œ€ ๋ณด์ƒ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Akshay ๐Ÿš€
@akshay_pachaar
Simplifying LLMs, AI Agents, RAG, and Machine Learning for you! โ€ข Co-founder @dailydoseofds_โ€ข BITS Pilani โ€ข 3 Patents โ€ข ex-AI Engineer @ LightningAI
๊ฐ€์ž… July 2012
505 ํŒ”๋กœ์ž‰ ์ค‘    291.6K ํŒฌ
everyone is sleeping on this new JSON extraction model! - open-weights - matches Gemini Flash 3.5 - while being 3x faster pulling structured data out of documents usually takes a chain of OCR, an LLM, and extra code to repair broken JSON. lift, from @datalabto, does all of this in a single step. you give lift a PDF or image along with a JSON schema, and get back a JSON object that matches that schema. the model reads every page of a document in one pass, so values that span multiple pages still come out right. any document you can describe in a schema works, from invoices to research papers. here's what you get with lift: - 90.2% field accuracy on 11,000 fields - 9B model, nearly matches Gemini Flash 3.5 at 3x the speed - built not to hallucinate; returns null if missing - self-hostable with vLLM or Hugging Face GitHub repo: (don't forget to star ๐ŸŒŸ)
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