Spaces:
Running
Running
File size: 24,618 Bytes
5511b8f f3e2722 5511b8f f3e2722 5511b8f f3e2722 8bf28d8 5511b8f f3e2722 8bf28d8 f3e2722 5511b8f f3e2722 5511b8f f3e2722 5511b8f f3e2722 5511b8f 8bf28d8 5511b8f f3e2722 8bf28d8 f3e2722 e99bda4 8bf28d8 e99bda4 5511b8f f3e2722 8bf28d8 f3e2722 8bf28d8 5511b8f 8bf28d8 f3e2722 8bf28d8 f3e2722 8bf28d8 f3e2722 8bf28d8 5511b8f f3e2722 8bf28d8 f3e2722 79d9284 f3e2722 79d9284 f3e2722 8bf28d8 f3e2722 79d9284 d5cdc10 79d9284 d5cdc10 79d9284 d5cdc10 79d9284 d5cdc10 79d9284 d5cdc10 79d9284 d5cdc10 79d9284 8bf28d8 f3e2722 8bf28d8 79d9284 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 79d9284 8bf28d8 5511b8f 8bf28d8 79d9284 8bf28d8 5511b8f 8bf28d8 79d9284 8bf28d8 5511b8f 8bf28d8 79d9284 5511b8f 8bf28d8 5511b8f f3e2722 8bf28d8 5511b8f 8bf28d8 5511b8f f3e2722 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 5511b8f 8bf28d8 f3e2722 8bf28d8 f3e2722 8bf28d8 79d9284 8bf28d8 f3e2722 e99bda4 8bf28d8 e99bda4 5511b8f 8bf28d8 5511b8f f3e2722 5511b8f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 | <!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MolForge: The Scientific Method as a Workflow</title>
<script src="https://cdn.tailwindcss.com"></script>
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700;800&family=JetBrains+Mono&display=swap" rel="stylesheet">
<style>
body {
font-family: 'Inter', -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
-webkit-font-smoothing: antialiased;
background-color: #ffffff;
color: #0f172a;
}
.prose-custom {
max-width: 70ch;
margin: 0 auto;
}
.shadcn-card {
border: 1px solid #e2e8f0;
background: #ffffff;
border-radius: 0.75rem;
box-shadow: 0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1);
}
.shadcn-badge {
background: #f1f5f9;
color: #475569;
font-size: 0.75rem;
font-weight: 600;
padding: 0.125rem 0.625rem;
border-radius: 9999px;
display: inline-flex;
align-items: center;
}
.mono {
font-family: 'JetBrains Mono', monospace;
}
.video-container {
position: relative;
padding-bottom: 56.25%;
height: 0;
overflow: hidden;
border-radius: 0.75rem;
border: 1px solid #e2e8f0;
}
.video-container iframe {
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
}
</style>
</head>
<body class="bg-white">
<!-- Navigation -->
<nav class="border-b sticky top-0 bg-white/80 backdrop-blur-md z-50">
<div class="max-w-5xl mx-auto px-6 h-16 flex items-center justify-between">
<span class="font-bold tracking-tight text-lg">MolForge</span>
<div class="flex gap-6 text-sm font-medium text-slate-600">
<a href="https://github.com/Adhitya-Vardhan/molt_lab" target="_blank" rel="noopener noreferrer" class="hover:text-black transition-colors">GitHub</a>
<a href="https://huggingface.co/spaces/Adhitya122/molforge" class="hover:text-black transition-colors">Space</a>
<a href="https://colab.research.google.com/drive/1c6npGkGNbbbd8XFNeS6zInBpopLnJ4W4?usp=sharing" target="_blank" rel="noopener noreferrer" class="hover:text-black transition-colors font-bold text-indigo-600">Try Training</a>
</div>
</div>
</nav>
<main class="max-w-5xl mx-auto px-6 py-20">
<!-- Header -->
<div class="mb-16 text-center">
<div class="flex justify-center gap-2 mb-6">
<span class="shadcn-badge bg-indigo-50 text-indigo-700 border border-indigo-100">Hackathon Submission</span>
<span class="shadcn-badge">Medical Oncology</span>
</div>
<h1 class="text-4xl md:text-6xl font-extrabold tracking-tight mb-6 leading-tight max-w-3xl mx-auto">
MolForge: The Scientific Method as a Workflow
</h1>
<p class="text-xl text-slate-500 mb-10 leading-relaxed max-w-2xl mx-auto">
How we trained an LLM to navigate a resource-constrained laboratory, optimize oncology drug candidates, and survive scientific "sunk-cost" traps.
</p>
<div class="flex items-center justify-center gap-4 text-sm text-slate-400 mb-12">
<div class="w-10 h-10 rounded-full bg-indigo-100 flex items-center justify-center text-indigo-600 font-bold">AV</div>
<div class="text-left">
<p class="font-semibold text-slate-900 leading-none mb-1">Adhitya Vardhan</p>
<p class="leading-none">OpenEnv Hackathon 2026 • 12 min read</p>
</div>
</div>
<!-- Video Section -->
<div class="max-w-3xl mx-auto mb-20">
<div class="video-container shadow-2xl">
<iframe src="https://www.youtube.com/embed/q8YoA0YhIn8" title="MolForge Explainer Video" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
</div>
<p class="mt-4 text-sm text-slate-400 italic">Watch the MolForge technical explainer (3:24)</p>
</div>
</div>
<!-- Introduction -->
<div class="prose prose-slate prose-lg max-w-none mb-24 leading-relaxed text-slate-700 border-b pb-20">
<h2 class="text-3xl font-bold text-slate-900 mb-6">Introduction</h2>
<p>
In traditional drug discovery tasks, LLMs are often asked to "generate a molecule" in a single shot. But science doesn't happen in a vacuum. It happens in the loop—through trial, error, and verification.
</p>
<p class="mt-4">
<strong>MolForge</strong> is a reinforcement learning environment that simulates a medical oncology discovery lab. It forces the model to navigate real-world constraints: limited budget, molecular toxicity, and synthesis complexity.
</p>
<div class="mt-12 p-8 bg-slate-900 text-slate-200 rounded-2xl shadow-lg">
<p class="text-indigo-400 font-bold mb-4 uppercase tracking-widest text-xs">Core Philosophy</p>
<p class="text-2xl font-medium leading-tight">
"The model is a trainable research agent inside a controlled scientific environment, not an oracle. It is judged by chemistry and biomedical verifiers, corrected by specialist feedback, and scored by a reward system that explains exactly where the path to a discovery failed."
</p>
</div>
</div>
<!-- The Scientific Verifier Stack -->
<section class="mb-32">
<div class="flex items-center gap-3 mb-8">
<div class="w-10 h-10 rounded-lg bg-emerald-600 flex items-center justify-center text-white font-bold">🧪</div>
<h2 class="text-3xl font-bold tracking-tight">The Scientific Verifier Stack</h2>
</div>
<p class="text-slate-600 mb-10 text-lg leading-relaxed">
MolForge doesn't just predict outcomes; it utilizes multiple simulation layers to ground the model's decisions in chemical and biological reality.
</p>
<div class="grid md:grid-cols-3 gap-6 mb-12">
<div class="shadcn-card p-8 bg-white hover:border-emerald-500 transition-all cursor-default group">
<div class="w-12 h-12 bg-emerald-50 text-emerald-600 rounded-xl flex items-center justify-center mb-6 text-xl">🧬</div>
<h4 class="font-bold text-lg mb-3">RDKit</h4>
<p class="text-sm text-slate-500 leading-relaxed italic">"Keeping molecules physically possible"</p>
<p class="text-sm text-slate-600 mt-4 leading-relaxed mb-6">
RDKit acts as the fundamental chemistry ruleset. It checks for molecular valency, ensures every edit is chemically plausible, and calculates core descriptors like Lipophilicity and TPSA.
</p>
<a href="https://www.rdkit.org" target="_blank" class="text-xs font-bold text-emerald-600 uppercase tracking-widest hover:underline">Visit RDKit.org →</a>
</div>
<div class="shadcn-card p-8 bg-white hover:border-blue-500 transition-all cursor-default group">
<div class="w-12 h-12 bg-blue-50 text-blue-600 rounded-xl flex items-center justify-center mb-6 text-xl">💊</div>
<h4 class="font-bold text-lg mb-3">TDC Oracles</h4>
<p class="text-sm text-slate-500 leading-relaxed italic">"Predicting biomedical fate"</p>
<p class="text-sm text-slate-600 mt-4 leading-relaxed mb-6">
Utilizing the Therapeutics Data Commons, MolForge predicts real-world ADMET properties, toxicity risks, and synthesizability scores (SA_Score) for every candidate.
</p>
<a href="https://tdcommons.ai" target="_blank" class="text-xs font-bold text-blue-600 uppercase tracking-widest hover:underline">Explore TDCommons.ai →</a>
</div>
<div class="shadcn-card p-8 bg-white hover:border-indigo-500 transition-all cursor-default">
<div class="w-12 h-12 bg-indigo-50 text-indigo-600 rounded-xl flex items-center justify-center mb-6 text-xl">🎯</div>
<h4 class="font-bold text-lg mb-3">Heuristic Docking</h4>
<p class="text-sm text-slate-500 leading-relaxed italic">"Simulating receptor-drug fit"</p>
<p class="text-sm text-slate-600 mt-4 leading-relaxed">
A fast, physics-inspired simulation that updates potency in milliseconds based on structural pocket matching and receptor complementarity.
</p>
</div>
</div>
<div class="p-8 bg-slate-50 border border-slate-200 rounded-2xl">
<h5 class="font-bold text-slate-900 mb-6 flex items-center gap-2">
<span class="w-2 h-2 bg-indigo-500 rounded-full"></span>
The 3 Rules of Potency Simulation
</h5>
<div class="grid md:grid-cols-3 gap-8">
<div class="space-y-2">
<p class="font-bold text-sm text-slate-800">1. Pocket Matching</p>
<p class="text-xs text-slate-500 leading-relaxed">Structural fit of the fragment (e.g., azaindole) into the KRAS G12C target pocket.</p>
</div>
<div class="space-y-2">
<p class="font-bold text-sm text-slate-800">2. Lipophilic Match</p>
<p class="text-xs text-slate-500 leading-relaxed">Targeting the ideal LogP of <strong>3.0</strong> for optimal binding without repulsive clashes.</p>
</div>
<div class="space-y-2">
<p class="font-bold text-sm text-slate-800">3. Polarity Match</p>
<p class="text-xs text-slate-500 leading-relaxed">Optimizing TPSA toward the ideal <strong>85.0</strong> to avoid polar clashes in hydrophobic pockets.</p>
</div>
</div>
</div>
</section>
<!-- The POMDP Architecture -->
<section class="mb-32">
<div class="flex items-center gap-3 mb-8">
<div class="w-10 h-10 rounded-lg bg-indigo-600 flex items-center justify-center text-white font-bold">1</div>
<h2 class="text-3xl font-bold tracking-tight">The POMDP Architecture</h2>
</div>
<p class="text-slate-600 mb-10 text-lg leading-relaxed">
MolForge is built as a <strong>Partially Observable Markov Decision Process (POMDP)</strong>. This means the agent never sees the "hidden truth" of the receptor. It only sees what its budget allows it to assay.
</p>
<div class="shadcn-card p-4 bg-slate-50 mb-12 border-dashed">
<img src="assets/molforge_architecture.png" alt="Architecture" class="rounded-lg w-full">
<p class="mt-4 text-center text-xs text-slate-400 font-medium tracking-wide">THE SCIENTIFIC FEEDBACK LOOP: VERIFIER-FIRST DESIGN</p>
</div>
<div class="grid md:grid-cols-2 gap-8">
<div class="space-y-4">
<h4 class="font-bold text-slate-900 border-b pb-2">The Hidden State</h4>
<ul class="space-y-3 text-slate-600 text-sm">
<li class="flex gap-2"><span>•</span> <strong>Ground Truth Potency:</strong> The exact hidden binding energy of the KRAS G12C pocket.</li>
<li class="flex gap-2"><span>•</span> <strong>Sunk-Cost Traps:</strong> Starting scaffolds that look promising but have hidden liabilities.</li>
<li class="flex gap-2"><span>•</span> <strong>Target Mutation:</strong> Late-stage shifts in the pocket (Level 2) that punish blind optimization.</li>
</ul>
</div>
<div class="space-y-4">
<h4 class="font-bold text-indigo-600 border-b pb-2">The Visible Evidence</h4>
<ul class="space-y-3 text-slate-600 text-sm">
<li class="flex gap-2"><span>•</span> <strong>RDKit & TDC Signals:</strong> Noisy, verifier-backed readings of Lipophilicity (LogP) and TPSA.</li>
<li class="flex gap-2"><span>•</span> <strong>Heuristic Docking:</strong> Fast simulations of pocket matching and receptor fit.</li>
<li class="flex gap-2"><span>•</span> <strong>Governance Vetoes:</strong> Objections from the Safety Specialist or Process Chemist.</li>
</ul>
</div>
</div>
</section>
<!-- Search Space & Scenarios -->
<section class="mb-32">
<div class="flex items-center gap-3 mb-8">
<div class="w-10 h-10 rounded-lg bg-indigo-600 flex items-center justify-center text-white font-bold">2</div>
<h2 class="text-3xl font-bold tracking-tight">The Molecular Search Space</h2>
</div>
<p class="text-slate-600 mb-10 text-lg leading-relaxed">
We don't ask the model to memorize molecules. We ask it to navigate a <strong>combinatorial space of 256 fragments</strong> across three starting scenarios.
</p>
<div class="grid grid-cols-2 md:grid-cols-4 gap-4 mb-12">
<div class="shadcn-card p-4 text-center">
<p class="text-xs font-bold text-slate-400 uppercase mb-2">Warhead</p>
<p class="text-sm font-semibold">4 Options</p>
</div>
<div class="shadcn-card p-4 text-center">
<p class="text-xs font-bold text-slate-400 uppercase mb-2">Hinge</p>
<p class="text-sm font-semibold">4 Options</p>
</div>
<div class="shadcn-card p-4 text-center">
<p class="text-xs font-bold text-slate-400 uppercase mb-2">Solvent Tail</p>
<p class="text-sm font-semibold">4 Options</p>
</div>
<div class="shadcn-card p-4 text-center">
<p class="text-xs font-bold text-slate-400 uppercase mb-2">Back Pocket</p>
<p class="text-sm font-semibold">4 Options</p>
</div>
</div>
<h3 class="text-xl font-bold mb-6">Benchmark Scenarios</h3>
<div class="shadcn-card overflow-hidden mb-12">
<table class="w-full text-left text-sm">
<thead class="bg-slate-50 border-b">
<tr>
<th class="px-6 py-4 font-semibold text-slate-900">Scenario</th>
<th class="px-6 py-4 font-semibold text-slate-900">Story</th>
<th class="px-6 py-4 font-semibold text-slate-900">Budget</th>
<th class="px-6 py-4 font-semibold text-slate-900">Difficulty</th>
</tr>
</thead>
<tbody class="divide-y">
<tr>
<td class="px-6 py-4 font-bold text-indigo-600">Level 0: Easy</td>
<td class="px-6 py-4 text-slate-500">Near-viable scaffold needs safety repair and evidence.</td>
<td class="px-6 py-4">3600</td>
<td class="px-6 py-4"><span class="shadcn-badge bg-emerald-50 text-emerald-700">Low</span></td>
</tr>
<tr>
<td class="px-6 py-4 font-bold text-indigo-600">Level 1: Medium</td>
<td class="px-6 py-4 text-slate-500">Potency, toxicity, and synthesis must be balanced.</td>
<td class="px-6 py-4">4300</td>
<td class="px-6 py-4"><span class="shadcn-badge bg-orange-50 text-orange-700">Moderate</span></td>
</tr>
<tr>
<td class="px-6 py-4 font-bold text-indigo-600">Level 2: Hard</td>
<td class="px-6 py-4 text-slate-500">Sunk-cost trap: starting series has hidden liability.</td>
<td class="px-6 py-4">5200</td>
<td class="px-6 py-4"><span class="shadcn-badge bg-red-50 text-red-700">Critical</span></td>
</tr>
</tbody>
</table>
</div>
</section>
<!-- Reward Design -->
<section class="mb-32">
<div class="flex items-center gap-3 mb-8">
<div class="w-10 h-10 rounded-lg bg-indigo-600 flex items-center justify-center text-white font-bold">3</div>
<h2 class="text-3xl font-bold tracking-tight">Reward Design: Beyond Scalar Scores</h2>
</div>
<p class="text-slate-600 mb-10 text-lg leading-relaxed">
Training for scientific rigor requires more than a "Good/Bad" signal. We use a <strong>decomposed reward system</strong> that mixes coarse shaping with sparse terminal bonuses.
</p>
<div class="grid md:grid-cols-3 gap-6 mb-12">
<div class="shadcn-card p-6 bg-slate-50 border-t-4 border-t-indigo-500">
<h4 class="font-bold mb-2 text-sm uppercase tracking-wider text-slate-500">Coarse Shaping</h4>
<p class="text-xs text-slate-500">Edit feedback avoids exact hidden deltas, forcing the model to rely on empirical assays.</p>
</div>
<div class="shadcn-card p-6 bg-slate-50 border-t-4 border-t-emerald-500">
<h4 class="font-bold mb-2 text-sm uppercase tracking-wider text-slate-500">Evidence Multipliers</h4>
<p class="text-xs text-slate-500">Submissions without current potency, toxicity, and synthesis support receive massive penalties.</p>
</div>
<div class="shadcn-card p-6 bg-slate-50 border-t-4 border-t-orange-500">
<h4 class="font-bold mb-2 text-sm uppercase tracking-wider text-slate-500">Budget Efficiency</h4>
<p class="text-xs text-slate-500">Small credits for valid evidence-backed submissions that use less than the allocated budget.</p>
</div>
</div>
<div class="p-6 bg-indigo-50 border border-indigo-100 rounded-xl text-sm">
<p class="font-bold text-indigo-700 mb-2 italic">"Curriculum mode is the RL warm-up engine—providing the breadcrumbs needed for the model to discover the submission bonus."</p>
</div>
</section>
<!-- Results -->
<section class="mb-32">
<div class="flex items-center gap-3 mb-8">
<div class="w-10 h-10 rounded-lg bg-indigo-600 flex items-center justify-center text-white font-bold">4</div>
<h2 class="text-3xl font-bold tracking-tight">Training Results</h2>
</div>
<div class="shadcn-card overflow-hidden mb-12">
<table class="w-full text-left text-sm">
<thead class="bg-slate-900 text-white">
<tr>
<th class="px-6 py-4 font-semibold uppercase tracking-wider text-[10px]">Difficulty</th>
<th class="px-6 py-4 font-semibold uppercase tracking-wider text-[10px]">Before (SFT)</th>
<th class="px-6 py-4 font-semibold uppercase tracking-wider text-[10px]">After (RL)</th>
<th class="px-6 py-4 font-semibold uppercase tracking-wider text-[10px]">Improvement</th>
</tr>
</thead>
<tbody class="divide-y">
<tr>
<td class="px-6 py-5 font-bold">Level 0: Easy</td>
<td class="px-6 py-5 text-slate-400">0.1167</td>
<td class="px-6 py-5 font-extrabold text-slate-900">0.1295</td>
<td class="px-6 py-5 text-emerald-600 font-black">+10.9%</td>
</tr>
<tr>
<td class="px-6 py-5 font-bold">Level 1: Medium</td>
<td class="px-6 py-5 text-slate-400">0.1167</td>
<td class="px-6 py-5 font-extrabold text-slate-900">0.1278</td>
<td class="px-6 py-5 text-emerald-600 font-black">+9.5%</td>
</tr>
<tr>
<td class="px-6 py-5 font-bold">Level 2: Hard</td>
<td class="px-6 py-5 text-slate-400">0.0800</td>
<td class="px-6 py-5 font-extrabold text-slate-900">0.0866</td>
<td class="px-6 py-5 text-emerald-600 font-black">+8.3%</td>
</tr>
</tbody>
</table>
</div>
<div class="grid md:grid-cols-2 gap-8">
<div class="shadcn-card p-6">
<img src="assets/reward_curve.png" alt="Reward Curve" class="rounded border mb-4">
<p class="text-xs font-bold text-slate-400 uppercase tracking-widest text-center">RL Training Progression</p>
</div>
<div class="shadcn-card p-6">
<img src="assets/Logs.png" alt="Logs" class="rounded border mb-4">
<p class="text-xs font-bold text-slate-400 uppercase tracking-widest text-center">Governance Action History</p>
</div>
</div>
</section>
<!-- Final Takeaway -->
<section class="mb-32 pt-20 border-t text-center">
<h2 class="text-4xl font-black mb-6 tracking-tight">Final Takeaway</h2>
<p class="text-slate-500 max-w-2xl mx-auto mb-12 text-lg leading-relaxed text-justify">
MolForge proves that scientific AI should not be built as a single-shot generator. By grounding the LLM in a <strong>closed-loop scientific environment</strong>, we can train models that respect budget, coordinate with specialists, and base their discoveries on verifiable evidence.
</p>
<div class="flex flex-wrap justify-center gap-4">
<a href="https://github.com/Adhitya-Vardhan/molt_lab" target="_blank" rel="noopener noreferrer" class="px-10 py-4 bg-slate-900 text-white font-bold rounded-xl hover:bg-slate-800 transition-all shadow-xl hover:-translate-y-1">Explore Code</a>
<a href="https://colab.research.google.com/drive/1c6npGkGNbbbd8XFNeS6zInBpopLnJ4W4?usp=sharing" target="_blank" rel="noopener noreferrer" class="px-10 py-4 bg-white border-2 border-slate-900 text-slate-900 font-bold rounded-xl hover:bg-slate-50 transition-all hover:-translate-y-1">Run Notebook</a>
</div>
<div class="mt-16 flex justify-center gap-8 text-sm font-bold text-slate-400">
<a href="https://huggingface.co/spaces/Adhitya122/molforge" class="hover:text-indigo-600 transition-colors uppercase tracking-widest">Space Deployment</a>
<a href="https://huggingface.co/Adhitya122/molforge-grpo-oncology" target="_blank" rel="noopener noreferrer" class="hover:text-indigo-600 transition-colors uppercase tracking-widest">Model Card</a>
</div>
</section>
<!-- Footer -->
<footer class="py-12 border-t text-xs text-slate-400 text-center">
<p>© 2026 MolForge Project • Built for the OpenEnv Hackathon</p>
</footer>
</main>
</body>
</html>
|