Organization card: banner, collections, models
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README.md
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---
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title: README
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---
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---
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title: README
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emoji: 🌴
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short_description: AI models built from the ground up, in Jamaica.
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---
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<img src="https://huggingface.co/spaces/CorxLabs/README/resolve/main/banner.png" alt="Corx Labs: AI models built from the ground up, in Jamaica" width="100%">
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**Corx Labs** is an independent AI lab in Westmoreland, Jamaica. We design, train and verify our own models end to
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end: architecture, tokenizer, training pipeline and evaluation, most of it on a single GPU.
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## 🗂️ Collections
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| | Collection | Inside |
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|:-:|---|---|
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| 💬 | [**Text Models**](https://huggingface.co/collections/CorxLabs/text-models-6ad400811d7073d767ebe7f1) | CorX language models, from 160M to 27B parameters, Jamaican Patois and English |
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| 🎤 | [**SVS Models**](https://huggingface.co/collections/CorxLabs/svs-models-6ad40082a6e143550bd7aaa6) | Singing-voice synthesis built on how a voice is physically made |
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| 🌀 | [**Weather Models**](https://huggingface.co/collections/CorxLabs/weather-models-6ad40082a150e48c970f176a) | Global weather and hurricane forecasting, scored on seasons it never trained on |
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## 💬 Text
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- [**CorX3.8-27B**](https://huggingface.co/Sigmandndnns/CorX3.8-27B): a 27B conversational model that speaks
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Jamaican Patois by default and switches to English when you do. Fully merged; load it and go.
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- [**CorX1.5-160M**](https://huggingface.co/Sigmandndnns/CorX1.5-160M): a ~158M-parameter language model whose
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architecture, tokenizer, pretraining and fine-tuning were all written and trained from scratch on one GPU.
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([v2 run](https://huggingface.co/Sigmandndnns/CorX1.5-160M-v2))
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## 🎤 Singing voice
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- [**TriStream-SVS-300M**](https://huggingface.co/Sigmandndnns/TriStream-SVS-300M): models a singing voice the
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way the body makes it, as three streams: the **glottal source** (pitch), the **vocal-tract filter** (who is
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singing, and which vowel) and **turbulent noise** (breath and fricatives).
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## 🌀 Weather and hurricanes
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- [**NatureV1**](https://huggingface.co/Sigmandndnns/NatureV1-500): an 89M-parameter model of the atmosphere on
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[iHELIX](https://pypi.org/project/ihelix/), an attention engine that works on the sphere rather than a flat grid.
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It forecasts global weather to five days and, for tropical cyclones, track, intensity, rapid intensification and
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landfall, each with an uncertainty.
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- Its hurricane physics, with **no neural network**, beats straight-line extrapolation and CLIPER at every lead
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from 6 to 120 hours on 4,447 forecasts of 407 storms in seasons it was never fitted on (2018, 2020-2022):
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| Track error (km) | 24 h | 48 h | 72 h | 120 h |
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|---|:-:|:-:|:-:|:-:|
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| Extrapolation | 179 | 442 | 751 | 1,417 |
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| CLIPER | 163 | 378 | 589 | 914 |
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| **NatureV1 physics** | **127** | **301** | **515** | **884** |
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Global AI models such as GraphCast and Pangu-Weather are still far better beyond 12 hours. Distilling them into
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NatureV1 is the next step, and every number on the model card says what it was measured on.
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```bash
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pip install naturev1 ihelix
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```
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## 🔗 Links
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[Website](https://www.corx-labs.com/) · [Developers](https://www.corx-labs.com/developers/) ·
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[naturev1 on PyPI](https://pypi.org/project/naturev1/) · [ihelix on PyPI](https://pypi.org/project/ihelix/)
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<p align="center"><sub>Built in Jamaica 🇯🇲</sub></p>
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banner.png
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Git LFS Details
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index.html
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</html>
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<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>Corx Labs</title>
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<style>
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:root { --bg:#07100b; --card:#0d1a12; --line:#1f3527; --text:#e8f1eb; --muted:#9cb5a5; --gold:#fed100; --green:#00b140; --sky:#7fd3ff; }
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* { box-sizing:border-box; }
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body { margin:0; background:var(--bg); color:var(--text); font:16px/1.6 Inter, system-ui, -apple-system, "Segoe UI", sans-serif; }
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main { max-width:1040px; margin:0 auto; padding:24px 16px 64px; }
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.banner { width:100%; border-radius:18px; display:block; border:1px solid var(--line); }
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p.lead { font-size:18px; color:var(--muted); margin:28px 0 8px; }
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p.lead b { color:var(--text); }
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h2 { font-size:15px; letter-spacing:.14em; text-transform:uppercase; color:var(--muted); margin:44px 0 14px; }
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.grid { display:grid; grid-template-columns:repeat(auto-fit, minmax(280px, 1fr)); gap:16px; }
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.card { background:var(--card); border:1px solid var(--line); border-radius:16px; padding:22px; display:flex; flex-direction:column; gap:10px; }
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.card ul { margin:4px 0 0; padding-left:18px; }
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.card li { margin:6px 0; }
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a { color:var(--gold); text-decoration:none; }
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a:hover { text-decoration:underline; }
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table { width:100%; border-collapse:collapse; font-variant-numeric:tabular-nums; margin-top:8px; }
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th, td { padding:10px 12px; border-bottom:1px solid var(--line); text-align:right; }
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th:first-child, td:first-child { text-align:left; }
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tr.us td { color:var(--gold); font-weight:700; }
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.note { color:var(--muted); font-size:14px; margin-top:10px; }
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code { background:#0f2217; border:1px solid var(--line); padding:3px 8px; border-radius:8px; color:var(--text); }
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footer { margin-top:56px; color:var(--muted); text-align:center; font-size:14px; }
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</style>
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</head>
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<body>
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<main>
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<img class="banner" src="banner.png" alt="Corx Labs: AI models built from the ground up, in Jamaica">
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<p class="lead"><b>Corx Labs</b> is an independent AI lab in Westmoreland, Jamaica. We design, train and verify our
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own models end to end: architecture, tokenizer, training pipeline and evaluation, most of it on a single GPU.</p>
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<h2>Collections</h2>
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<div class="grid">
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<section class="card">
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<h3><span class="dot" style="background:var(--gold)"></span>Text</h3>
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<ul>
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<li><a href="https://huggingface.co/Sigmandndnns/CorX3.8-27B"><b>CorX3.8-27B</b></a>: 27B, speaks Jamaican Patois by default and English when you do.</li>
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<li><a href="https://huggingface.co/Sigmandndnns/CorX1.5-160M"><b>CorX1.5-160M</b></a>: ~158M, architecture, tokenizer and training all written from scratch on one GPU.</li>
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</ul>
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<a class="more" href="https://huggingface.co/collections/CorxLabs/text-models-6ad400811d7073d767ebe7f1">Text Models collection →</a>
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</section>
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<section class="card">
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<h3><span class="dot" style="background:var(--green)"></span>Singing voice</h3>
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<ul>
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<li><a href="https://huggingface.co/Sigmandndnns/TriStream-SVS-300M"><b>TriStream-SVS-300M</b></a>: a voice as the body makes it: glottal source (pitch), vocal-tract filter (who and which vowel), breath noise.</li>
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</ul>
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<a class="more" href="https://huggingface.co/collections/CorxLabs/svs-models-6ad40082a6e143550bd7aaa6">SVS Models collection →</a>
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</section>
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<section class="card">
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<h3><span class="dot" style="background:var(--sky)"></span>Weather & hurricanes</h3>
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<ul>
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<li><a href="https://huggingface.co/Sigmandndnns/NatureV1-500"><b>NatureV1</b></a>: 89M-parameter atmosphere model on the iHELIX spherical attention engine: global weather to five days; hurricane track, intensity, rapid intensification and landfall, each with an uncertainty.</li>
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</ul>
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<a class="more" href="https://huggingface.co/collections/CorxLabs/weather-models-6ad40082a150e48c970f176a">Weather Models collection →</a>
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</section>
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</div>
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<h2>Hurricane physics, scored on seasons it never saw</h2>
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<div class="card">
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<p>NatureV1's hurricane physics, with no neural network, against extrapolation and CLIPER on 4,447 forecasts of
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407 storms from 2018 and 2020-2022, seasons it was never fitted on.</p>
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<div class="scroll">
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<table>
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<tr><th>Track error (km)</th><th>24 h</th><th>48 h</th><th>72 h</th><th>120 h</th></tr>
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<tr><td>Extrapolation</td><td>179</td><td>442</td><td>751</td><td>1,417</td></tr>
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<tr><td>CLIPER</td><td>163</td><td>378</td><td>589</td><td>914</td></tr>
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<tr class="us"><td>NatureV1 physics</td><td>127</td><td>301</td><td>515</td><td>884</td></tr>
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</table>
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</div>
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<p class="note">Global AI models such as GraphCast and Pangu-Weather are still far better beyond 12 hours;
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distilling them into NatureV1 is the next step.</p>
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<p><code>pip install naturev1 ihelix</code></p>
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</div>
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<footer>
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<a href="https://www.corx-labs.com/">Website</a> · <a href="https://www.corx-labs.com/developers/">Developers</a> ·
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<a href="https://pypi.org/project/naturev1/">naturev1</a> · <a href="https://pypi.org/project/ihelix/">ihelix</a>
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<br>Built in Jamaica 🇯🇲
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</footer>
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</main>
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</body>
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</html>
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