There are several scripts for doing this. I might encourage you to checkout our Hello LTR library of notebooks, which has a ranklib training driver, and helpers to log training data, train a model w/ Ranklib, and search with it. I am using this code for my LTR contributions AI Powered Search
http://github.com/o19s/hello-ltr But if you just care about the conversion, check out this code. It's adapted / inspired by code written by Christine Poerschke with her Ltr For Bees demo / talk https://github.com/o19s/hello-ltr/blob/master/ltr/helpers/convert.py Best -Doug On Wed, Jun 17, 2020 at 12:46 PM gnandre <arnoldbron...@gmail.com> wrote: > Hi, > > Before I start writing my own implementation for converting RankLib's model > output format to Solr LTR model format for my own use cases, I just wanted > to check if there is any work done on this front already. Any references > are welcome. > -- *Doug Turnbull **| CTO* | OpenSource Connections <http://opensourceconnections.com>, LLC | 240.476.9983 Author: Relevant Search <http://manning.com/turnbull>; Contributor: *AI Powered Search <http://aipoweredsearch.com>* This e-mail and all contents, including attachments, is considered to be Company Confidential unless explicitly stated otherwise, regardless of whether attachments are marked as such.
