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| <title>ThingsAI - Smart & Efficient SLMs</title> |
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| |
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| |
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| margin-bottom: 20px; |
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| |
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| |
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| font-size: 0.95rem; |
| transition: all 0.25s; |
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| |
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| color: #818cf8; |
| transform: translateX(3px); |
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| |
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| display: inline-block; |
| padding: 6px 16px; |
| border-radius: 100px; |
| font-size: 0.8rem; |
| font-weight: 600; |
| border: 1px solid rgba(251, 191, 36, 0.2); |
| } |
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| |
| .card summary { |
| list-style: none; |
| cursor: pointer; |
| outline: none; |
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| .card summary::-webkit-details-marker { display: none; } |
| |
| .card summary::after { |
| content: "+"; |
| position: absolute; |
| right: 36px; |
| top: 36px; |
| font-size: 1.5rem; |
| font-weight: 300; |
| color: var(--text-secondary); |
| transition: transform 0.3s ease; |
| } |
| |
| .card[open] summary::after { |
| transform: rotate(45deg); |
| color: #ffffff; |
| } |
| |
| .card-details { |
| padding-top: 24px; |
| border-top: 1px solid rgba(255, 255, 255, 0.05); |
| animation: fadeIn 0.4s ease-out forwards; |
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| |
| @keyframes fadeIn { |
| from { opacity: 0; transform: translateY(4px); } |
| to { opacity: 1; transform: translateY(0); } |
| } |
| |
| .split-variants { |
| display: flex; |
| gap: 12px; |
| } |
| |
| .variant { |
| flex: 1; |
| display: flex; |
| align-items: center; |
| justify-content: center; |
| gap: 8px; |
| padding: 14px; |
| border-radius: var(--radius-sm); |
| font-weight: 600; |
| font-size: 0.9rem; |
| text-decoration: none; |
| color: white; |
| transition: all 0.25s; |
| border: 1px solid rgba(255,255,255,0.05); |
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| overflow: hidden; |
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| |
| .variant::after { |
| content: "↗"; |
| font-size: 0.8em; |
| opacity: 0; |
| transform: translateX(-5px); |
| transition: all 0.2s; |
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| |
| .variant:hover::after { |
| opacity: 1; |
| transform: translateX(0); |
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| |
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| transform: translateY(-2px); |
| box-shadow: 0 10px 20px rgba(0,0,0,0.2); |
| filter: brightness(1.1); |
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| |
| .variant.base { background: rgba(37, 99, 235, 0.15); border-color: rgba(37, 99, 235, 0.3); color: #3b82f6; } |
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| |
| .variant.bilingual { background: rgba(5, 150, 105, 0.15); border-color: rgba(5, 150, 105, 0.3); color: #10b981; } |
| .variant.bilingual:hover { background: rgba(5, 150, 105, 0.25); } |
| |
| .variant.instruct { background: rgba(124, 58, 237, 0.15); border-color: rgba(124, 58, 237, 0.3); color: #8b5cf6; } |
| .variant.instruct:hover { background: rgba(124, 58, 237, 0.25); } |
| |
| .variant.base-270 { background: rgba(217, 119, 6, 0.15); border-color: rgba(217, 119, 6, 0.3); color: #f59e0b; } |
| .variant.base-270:hover { background: rgba(217, 119, 6, 0.25); } |
| |
| |
| .features-grid { |
| display: grid; |
| grid-template-columns: repeat(auto-fit, minmax(260px, 1fr)); |
| gap: 32px; |
| } |
| |
| .feature-card { |
| background: rgba(255, 255, 255, 0.01); |
| border: 1px solid var(--border); |
| border-radius: var(--radius-md); |
| padding: 36px; |
| transition: all 0.3s; |
| } |
| |
| .feature-card:hover { |
| border-color: rgba(255, 255, 255, 0.1); |
| background: rgba(255, 255, 255, 0.02); |
| } |
| |
| .feature-card .icon { |
| font-size: 1.8rem; |
| margin-bottom: 24px; |
| display: inline-flex; |
| align-items: center; |
| justify-content: center; |
| width: 52px; |
| height: 52px; |
| background: rgba(255, 255, 255, 0.02); |
| border-radius: var(--radius-sm); |
| border: 1px solid var(--border); |
| } |
| |
| .feature-card h4 { |
| font-size: 1.25rem; |
| font-weight: 700; |
| margin-bottom: 14px; |
| color: #ffffff; |
| letter-spacing: -0.01em; |
| } |
| |
| .feature-card p { |
| font-size: 0.95rem; |
| color: var(--text-secondary); |
| line-height: 1.6; |
| } |
| |
| |
| .table-container { |
| border-radius: var(--radius-lg); |
| border: 1px solid var(--border); |
| overflow-x: auto; |
| background: var(--surface); |
| box-shadow: 0 40px 80px rgba(0, 0, 0, 0.3), inset 0 1px 0 rgba(255,255,255,0.03); |
| backdrop-filter: blur(20px); |
| -webkit-backdrop-filter: blur(20px); |
| } |
| |
| .custom-table { |
| width: 100%; |
| border-collapse: collapse; |
| text-align: left; |
| } |
| |
| .custom-table th { |
| padding: 24px 32px; |
| font-size: 0.75rem; |
| font-weight: 700; |
| text-transform: uppercase; |
| letter-spacing: 0.1em; |
| color: var(--text-secondary); |
| background: rgba(255, 255, 255, 0.02); |
| border-bottom: 1px solid var(--border); |
| } |
| |
| .custom-table td { |
| padding: 22px 32px; |
| font-size: 0.98rem; |
| border-bottom: 1px solid rgba(255,255,255,0.03); |
| color: var(--text-secondary); |
| transition: all 0.2s; |
| } |
| |
| .custom-table tr:last-child td { border-bottom: none; } |
| |
| .custom-table tr:hover td { |
| background: rgba(255, 255, 255, 0.01); |
| color: #ffffff; |
| } |
| |
| .table-link { |
| color: #ffffff; |
| text-decoration: none; |
| font-weight: 600; |
| display: inline-flex; |
| align-items: center; |
| gap: 8px; |
| transition: color 0.2s; |
| } |
| |
| .table-link:hover { |
| color: #818cf8; |
| } |
| |
| |
| footer { |
| border-top: 1px solid var(--border); |
| padding: 56px 0; |
| margin-top: 140px; |
| background: rgba(2, 0, 10, 0.8); |
| } |
| |
| .footer-content { |
| display: flex; |
| justify-content: space-between; |
| align-items: center; |
| font-size: 0.9rem; |
| color: var(--text-secondary); |
| flex-wrap: wrap; |
| gap: 24px; |
| } |
| |
| .footer-content span { |
| font-weight: 700; |
| color: #ffffff; |
| } |
| |
| |
| @media (max-width: 968px) { |
| .hero { padding: 90px 0 60px; } |
| .hero h1 { font-size: 3.5rem; } |
| .cards-grid { grid-template-columns: 1fr; } |
| .footer-content { flex-direction: column; text-align: center; } |
| } |
| |
| @media (max-width: 580px) { |
| .container { padding: 0 20px; } |
| .hero h1 { font-size: 2.4rem; } |
| .subtitle { font-size: 1.1rem; } |
| .chat-pipe { |
| flex-direction: column; |
| border-radius: 20px; |
| padding: 8px; |
| gap: 12px; |
| } |
| .chat-pipe input { padding: 12px 8px; } |
| .chat-pipe button { width: 100%; justify-content: center; border-radius: 14px; } |
| .split-variants { flex-direction: column; } |
| .custom-table th, .custom-table td { padding: 16px 20px; } |
| } |
| </style> |
| </head> |
| <body> |
|
|
| <div class="page-wrapper"> |
|
|
| <nav class="navbar"> |
| <div class="container nav-container"> |
| <div class="logo">ThingsAI</div> |
| </div> |
| </nav> |
|
|
| <header class="hero"> |
| <div class="container"> |
| <span class="badge">✨ Quark v0.1 released</span> |
| |
| <h1>Next-gen intelligence, <span>scaled down.</span></h1> |
|
|
| <p class="subtitle"> |
| Building highly efficient, logic-driven Small Language Models that run natively on edge hardware and consumer devices. |
| </p> |
|
|
| <form action="https://chat.things-ai.org/" target="_blank" class="chat-pipe"> |
| <input type="text" placeholder="Ask Quark anything..." required name="ignore_message"> |
| <button type="submit"> |
| <span>Launch Chat</span> |
| <svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2.5"><path d="M5 12h14M12 5l7 7-7 7"/></svg> |
| </button> |
| </form> |
| </div> |
| </header> |
|
|
| <main class="container"> |
| |
| <section class="section"> |
| <div class="section-header"> |
| <h2>Available Models</h2> |
| <span class="line"></span> |
| </div> |
|
|
| <div class="cards-grid"> |
| |
| <details class="card"> |
| <summary> |
| <div class="card-tag">Bilingual</div> |
| <h3>Quark-135M <span class="param-badge">135M</span></h3> |
| <p class="card-desc">A lightweight bilingual language model optimized for speed and localized logic. Click to expand variants.</p> |
| <p class="card-tech">Features GQA, SwiGLU, RMSNorm, and RoPE. Trained on 50B+ tokens of ultra-curated data.</p> |
| </summary> |
| <div class="card-details"> |
| <div class="split-variants"> |
| <a href="https://huggingface.co/ThingAI/Quark-135m" target="_blank" class="variant base">🧠 Base</a> |
| <a href="https://huggingface.co/ThingAI/Quark-135m-Bilingual" target="_blank" class="variant bilingual">🌐 Bilingual</a> |
| </div> |
| </div> |
| </details> |
|
|
| <details class="card highlight"> |
| <summary> |
| <div class="card-tag status">Featured Model</div> |
| <h3>Quark-270M <span class="param-badge">270M</span></h3> |
| <p class="card-desc">Our scaled small model featuring 32 layers and 768 hidden dimensions for advanced reasoning capabilities.</p> |
| <p class="card-tech">Equipped with a dense 65K vocabulary. Specially designed for multi-turn instruct fine-tuning.</p> |
| </summary> |
| <div class="card-details"> |
| <div class="split-variants"> |
| <a href="https://huggingface.co/ThingAI/Quark-270m-Instruct" target="_blank" class="variant instruct">🚀 Instruct</a> |
| <a href="https://huggingface.co/ThingAI/Quark-270m-Base" target="_blank" class="variant base-270">⚙️ Base</a> |
| </div> |
| </div> |
| </details> |
|
|
| <article class="card"> |
| <div class="card-tag old">Legacy</div> |
| <h3>Quark-50M <span class="param-badge">50M</span></h3> |
| <p class="card-desc">Our compact 50M parameter model — engineered for extremely hyper-low resource systems.</p> |
| <p class="card-tech">Lightweight and highly volatile, ideal for basic sequence prediction and embedded units.</p> |
| <a href="https://huggingface.co/ThingAI/Quark-50m" target="_blank" class="card-link">Explore Weights →</a> |
| </article> |
|
|
| <article class="card"> |
| <div class="card-tag special">Specialized</div> |
| <h3>Quark-Math-Code <span class="param-badge">36M</span></h3> |
| <p class="card-desc">Deep-thin experimental architecture engineered specifically for STEM tracking and math code parsing.</p> |
| <p class="card-tech">14 layers. Actively pre-training on a 5B token target with embedded Chain-of-Thought datasets.</p> |
| <span class="card-status-btn" style="background: rgba(251, 191, 36, 0.05); color: #fbbf24; cursor: default;">Training Active</span> |
| </article> |
|
|
| <article class="card"> |
| <div class="card-tag safety">Safety Matrix</div> |
| <h3>Quark-Mod <span class="param-badge">Classifier</span></h3> |
| <p class="card-desc">A high-throughput multi-label moderation engine covering 9 toxicity and cyber-safety categories.</p> |
| <p class="card-tech">Detects: toxic, severe_toxic, obscene, threat, insult, identity_hate, and advanced content exploits.</p> |
| <a href="https://huggingface.co/ThingAI/Quark-Mod" target="_blank" class="card-link">View Classifier →</a> |
| </article> |
| </div> |
| </section> |
|
|
| <section class="section"> |
| <div class="section-header"> |
| <h2>Core Focus Areas</h2> |
| <span class="line"></span> |
| </div> |
|
|
| <div class="features-grid"> |
| <div class="feature-card"> |
| <div class="icon">⚡</div> |
| <h4>Hyper-Efficient</h4> |
| <p>Mastering sub-1B parameters using Grouped-Query Attention (GQA) architectures.</p> |
| </div> |
|
|
| <div class="feature-card"> |
| <div class="icon">🧠</div> |
| <h4>Embedded CoT</h4> |
| <p>Integrating step-by-step reasoning logic directly into the pre-training tokens.</p> |
| </div> |
|
|
| <div class="feature-card"> |
| <div class="icon">🌍</div> |
| <h4>Bilingual Focus</h4> |
| <p>High-density blending of localized Italian, English, and technical STEM pipelines.</p> |
| </div> |
|
|
| <div class="feature-card"> |
| <div class="icon">💻</div> |
| <h4>True Open Source</h4> |
| <p>All weights, configurations, and baseline streaming datasets are entirely open to the world.</p> |
| </div> |
| </div> |
| </section> |
|
|
| <section class="section"> |
| <div class="section-header"> |
| <h2>Open Ecosystem Index</h2> |
| <span class="line"></span> |
| </div> |
|
|
| <div class="table-container"> |
| <table class="custom-table"> |
| <thead> |
| <tr> |
| <th>Repository Object</th> |
| <th>Distribution Target</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr> |
| <td><a href="https://huggingface.co/ThingAI/Quark-135m" target="_blank" class="table-link">📚 Quark-135M Base</a></td> |
| <td>Foundational localized small baseline language matrix.</td> |
| </tr> |
| <tr> |
| <td><a href="https://huggingface.co/ThingAI/Quark-135m-Bilingual" target="_blank" class="table-link">🌐 Quark-135M Bilingual</a></td> |
| <td>Bilingual (IT + EN) checkpoint trained on balanced multi-source pools.</td> |
| </tr> |
| <tr> |
| <td><a href="https://huggingface.co/ThingAI/Quark-270m-Instruct" target="_blank" class="table-link">🚀 Quark-270M Instruct</a></td> |
| <td>Multi-turn conversation alignment model with strict formatting safety.</td> |
| </tr> |
| <tr> |
| <td><a href="https://huggingface.co/ThingAI/Quark-270m-Base" target="_blank" class="table-link">⚙️ Quark-270M Base</a></td> |
| <td>Base engine ready for specialized downstream task tokenization.</td> |
| </tr> |
| <tr> |
| <td><a href="https://huggingface.co/ThingAI/Quark-50m" target="_blank" class="table-link">📦 Quark-50M</a></td> |
| <td>Legacy foundational checkpoint for exploratory sequence architectures.</td> |
| </tr> |
| <tr> |
| <td><a href="https://huggingface.co/ThingAI/Quark-Mod" target="_blank" class="table-link">🛡️ Quark-Mod</a></td> |
| <td>Production safety guardrail classifier for modern pipeline filtering.</td> |
| </tr> |
| <tr> |
| <td><a href="https://huggingface.co/collections/ThingAI/quark-v01" target="_blank" class="table-link">⚡️ Complete Collection (v0.1)</a></td> |
| <td>Unified access hub to all current generation architectural releases.</td> |
| </tr> |
| <tr> |
| <td><a href="https://github.com/overcastlab" target="_blank" class="table-link">💻 GitHub Organization</a></td> |
| <td>Training codebases, data streaming pipelines, and infrastructure layers.</td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| </section> |
|
|
| </main> |
|
|
| <footer> |
| <div class="container footer-content"> |
| <p>© 2026 <span>ThingsAI Labs</span>. Architectural weights distributed under Apache-2.0.</p> |
| <p>Engineered for absolute edge efficiency.</p> |
| </div> |
| </footer> |
|
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| </div> |
| </body> |
| </html> |
