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rerankers

A lightweight unified API for various reranking models. Developed by @bclavie as a member of answer.ai

Welcome to rerankers ! Our goal is to provide users with a simple API to use any reranking models.

Updates

• v0.3.1: T5 bugfix and native default support for new Portuguese T5 rerankers.


• v0.3.0: 🆕 Many changes! Experimental support for

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Based. Semantic chunking is overrated. Especially when you write a super regex that leverages all possible boundary cues and heuristics to segment text accurately without the need for complex language models. Just think about the speed and the hosting cost. This 50-line, 2490-character regex is as powerful as it can be within the limitations of... See more

Open source platform for developing, monitoring, and debugging LLM apps https://t.co/IsNrD2V55I

A treasure trove just dropped. Transformer family V2: a very comprehensive survey of the latest and greatest in modern LLM’s backbone. Covers lots of advanced features like longer context memory, external memory, recurrence, adaptive & efficient attention, and Transformer+RL.... See more

🦆 Docling reaches 12.3K⭐️ There are now a few parsers for LLMs out there but this is one of the most popular. Supports PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown. Other features include advanced PDF understanding, integrations, OCR for scanned... See more

Boosting annotator efficiency with Large Language Models

In July and August, we released LLM-assisted recipes for data annotation and prompt engineering:

• NER: ner.llm.correct, ner.llm.fetch


• Spancat: spans.llm.correct, spans.llm.fetch


• Textcat: textcat.llm.correct, textcat.llm.fetch


• Prompt engineering and terms: ab.llm.tournament terms.llm.fetch

Prodigy's... See more

LLM pipeline monitoring and optimization platform https://t.co/rQuHK5Sdry

https://t.co/HI2T2cLwYb You can now try out the NLP Input Component on my Portfolio. I also included code snippets for better understanding how it works :) https://t.co/XkVNdsi6dj