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| title: KeelCore |
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| <p align="center"> |
| <img src="https://huggingface.co/spaces/KeelCore/README/resolve/main/banner.png" alt="KeelCore: one compact base, small adapters, built to run on your device" width="100%"> |
| </p> |
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| **KeelCore is one compact base model plus many small LoRA adapters.** We pretrain the base once. A new capability then arrives as a small adapter, not a new model, so you download the base once and add only the adapters you need. |
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| <p align="center"> |
| <b><a href="https://huggingface.co/KeelCore/KeelCore-750M" target="_blank" rel="noopener noreferrer">KeelCore-750M</a></b> · <b><a href="https://saravanan-a-r.github.io/KeelCore/" target="_blank" rel="noopener noreferrer">Technical report</a></b> · <b><a href="https://github.com/saravanan-a-r/KeelCore" target="_blank" rel="noopener noreferrer">GitHub</a></b> · <b><a href="#contact">Contact</a></b> |
| </p> |
|
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| ## Models |
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|
| | Model | Status | Details | |
| |---|---|---| |
| | **<a href="https://huggingface.co/KeelCore/KeelCore-750M" target="_blank" rel="noopener noreferrer">KeelCore‑750M</a>** | Base model | 752M parameters, encoder–decoder, 2,048-token context. English, code and command line. | |
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| Benchmarks, including where we trail models trained on larger budgets, are on the model card. |
|
|
| ## Adapters |
|
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| An adapter is a small, separate download that works only with the base it was trained on. You install the base once, then pick the adapters you need. |
|
|
| | Adapter | Status | |
| |---|---| |
| | Text-rewriting adapters | In training | |
| | Other domains, for example legal and marketing writing | Planned (no dates) | |
|
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| We plan one repository per adapter, named after the base and the task (`KeelCore-750M-<task>`), possibly at more than one LoRA rank. This page will list each one when it is released. |
|
|
| ## Why this approach |
|
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| * **One base.** A single pretrained encoder–decoder with a tokenizer built for English prose, source code and command-line text. |
| * **Small adapters.** A rank-16 LoRA adapter trains about 18.3M parameters, 2.4% of the base, while the base weights stay frozen. |
| * **Runs on your device.** A weight-only int8 ONNX export (0.76 GB) runs in a web browser through ONNX Runtime Web. Because that runtime could not load LoRA adapters, we contributed the support ourselves: a `LoraAdapter` API and an `activeLoraAdapters` run option, merged in October 2026 (<a href="https://github.com/microsoft/onnxruntime/pull/32886" target="_blank" rel="noopener noreferrer">microsoft/onnxruntime#32886</a>). |
|
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| ## Built with KeelCore |
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| **EchoMeBetter** is the first product built on KeelCore: a browser extension that runs the base and its text-rewriting adapters on your device. It is one application, not the purpose of KeelCore, which is a general base for adapters. |
|
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| ## License |
|
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| Models are released under the **KeelCore License, Version 1.0**: personal use through the official EchoMeBetter extension and noncommercial research, which requires citing the project. Commercial use, use by an organization and any use outside the extension need a separate written agreement. Adapters follow the same terms unless their repository says otherwise. |
|
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| ## Contact |
|
|
| **Saravanan A R** · <a href="https://www.linkedin.com/in/saravanan-a-r/" target="_blank" rel="noopener noreferrer">LinkedIn</a> · <a href="https://github.com/saravanan-a-r" target="_blank" rel="noopener noreferrer">GitHub</a> |
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| Commercial licensing and partnerships: sararavi.ar@gmail.com |
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