KeelCore Copyright (c) 2026 Saravanan A R. All rights reserved. https://github.com/saravanan-a-r/KeelCore KeelCore is a base model for LoRA adapters. The EchoMeBetter browser extension runs it together with its adapters, on your device. Both are covered by the KeelCore License, Version 1.0 (Personal and Research Use), dated October 28, 2026. See LICENSE. That file controls; this notice is a summary. Individuals may use KeelCore, at no cost, for their own writing (including writing for their own job or studies) and for noncommercial research, only through the official EchoMeBetter browser extension. Commercial use, use by or for an organization, any use outside the official extension, and purchase of the model require a separate written agreement with the copyright holder. See COMMERCIAL_LICENSE.md. "KeelCore" and "EchoMeBetter" are names used by the copyright holder for this project; the license gives no right to use them (Section 6.3). -------------------------------------------------------------------------- REQUIRED CITATION FOR RESEARCH -------------------------------------------------------------------------- Section 4 of the license requires every publication or presentation of research that uses KeelCore (papers, theses, reports, articles, posts, slides, and talks) to cite the project in a reasonably prominent place. Use one of these forms, or an equivalent one with the same information: Plain text: KeelCore (2026) by Saravanan A R. https://github.com/saravanan-a-r/KeelCore Academic / BibTeX citation: @software{keelcore2026, author = {Saravanan A R}, title = {KeelCore: A 752M Encoder-Decoder Base Model for LoRA Adapters}, year = {2026}, url = {https://github.com/saravanan-a-r/KeelCore} } Citing the project does not imply that its author endorses your work. -------------------------------------------------------------------------- TRAINING DATA ATTRIBUTION -------------------------------------------------------------------------- The KeelCore model is pretrained on the following datasets, each used under its own license. These attributions are given as those licenses ask; they do not grant any right in the model (Section 15.5 of the license). * FineWeb-Edu, by Hugging Face. https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu Open Data Commons Attribution License (ODC-By) v1.0, also subject to the Common Crawl Terms of Use. * C4 (Colossal Clean Crawled Corpus), English, as released by the Allen Institute for AI. https://huggingface.co/datasets/allenai/c4 Open Data Commons Attribution License (ODC-By) v1.0, also subject to the Common Crawl Terms of Use. * Cosmopedia, by Hugging Face. https://huggingface.co/datasets/HuggingFaceTB/cosmopedia Apache License 2.0. * PG-19, by DeepMind, books from Project Gutenberg published before 1919. https://github.com/google-deepmind/pg19 Apache License 2.0. * GitHub Code Clean, by CodeParrot, permissively licensed subsets only (MIT, Apache-2.0 and BSD-3-Clause source files). https://huggingface.co/datasets/codeparrot/github-code-clean * tldr-pages, by the tldr-pages contributors. https://github.com/tldr-pages/tldr Creative Commons Attribution 4.0 International (CC BY 4.0). * cheat/cheatsheets, by the cheat contributors. https://github.com/cheat/cheatsheets CC0 1.0 Universal.