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README.md

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-title: README
-emoji: 🏆
-colorFrom: pink
+title: KeelCore
+emoji: ⚓
+colorFrom: blue
 colorTo: yellow
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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+<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>
+
+**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.
+
+<p align="center">
+  <b><a href="https://huggingface.co/KeelCore/KeelCore-750M" target="_blank" rel="noopener noreferrer">KeelCore-750M</a></b> &nbsp;·&nbsp; <b><a href="https://saravanan-a-r.github.io/KeelCore/" target="_blank" rel="noopener noreferrer">Technical report</a></b> &nbsp;·&nbsp; <b><a href="https://github.com/saravanan-a-r/KeelCore" target="_blank" rel="noopener noreferrer">GitHub</a></b> &nbsp;·&nbsp; <b><a href="#contact">Contact</a></b>
+</p>
+
+## Models
+
+| 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. |
+
+Benchmarks, including where we trail models trained on larger budgets, are on the model card.
+
+## Adapters
+
+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) |
+
+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
+
+* **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>).
+
+## Built with KeelCore
+
+**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.
+
+## License
+
+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.
+
+## 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>
+
+Commercial licensing and partnerships: sararavi.ar@gmail.com