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<!DOCTYPE html>
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<title>👻 GhostPack: Veo 3-Level Video Sorcery 😈</title>
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<link rel="icon" href="https://huggingface.co/spaces/ghostai1/GhostPack/resolve/main/ghostpack_logo.png">
</head>
<body>
<!-- Navbar -->
<nav class="navbar navbar-expand-lg navbar-dark fixed-top">
<div class="container">
<a class="navbar-brand" href="#">👻 GhostPack</a>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
<span class="navbar-toggler-icon"></span>
</button>
<div class="collapse navbar-collapse" id="navbarNav">
<ul class="navbar-nav ms-auto">
<li class="nav-item"><a class="nav-link" href="#home">Home</a></li>
<li class="nav-item"><a class="nav-link" href="#features">Features</a></li>
<li class="nav-item"><a class="nav-link" href="#optimizations">Math Sorcery</a></li>
<li class="nav-item"><a class="nav-link" href="#future">Future</a></li>
<li class="nav-item"><a class="nav-link" href="#installation">Installation</a></li>
<li class="nav-item"><a class="nav-link" href="#usage">Usage</a></li>
<li class="nav-item"><a class="nav-link" href="#model">Model Card</a></li>
</ul>
</div>
</div>
</nav>
<!-- Hero Section -->
<section id="home" class="hero-section text-center text-white">
<div class="container">
<h1 class="display-3 animate__animated animate__zoomIn">👻 GhostPack</h1>
<p class="lead animate__animated animate__fadeIn animate__delay-1s">Veo 3-Level Video Sorcery Haunts Laptops with 8GB RAM! 😈🚀</p>
<p class="animate__animated animate__fadeIn animate__delay-2s">Unleash photorealistic videos with ghostai1’s math wizardry on GPUs ≥6GB VRAM.</p>
<a href="#installation" class="btn btn-ghost btn-lg animate__animated animate__pulse animate__delay-3s">Summon Now 🛠️</a>
<a href="https://github.com/ghostai1/GhostPack" class="btn btn-outline-ghost btn-lg animate__animated animate__pulse animate__delay-3s" target="_blank">GitHub 🌟</a>
</div>
</section>
<!-- Features Section -->
<section id="features" class="py-5 bg-dark text-white">
<div class="container">
<h2 class="text-center mb-5 animate__animated animate__fadeIn">✨ Spectral Features</h2>
<div class="row row-cols-1 row-cols-md-3 g-4">
<div class="col">
<div class="card bg-ghost-card h-100" data-bs-toggle="tooltip" title="Rivals industry leaders like Veo 3">
<div class="card-body">
<h3 class="card-title">📹 Veo 3-Level AI</h3>
<p class="card-text">Hyper-realistic, fluid videos via next-frame prediction, running on 8GB RAM laptops.</p>
</div>
</div>
</div>
<div class="col">
<div class="card bg-ghost-card h-100" data-bs-toggle="tooltip" title="Blazing fast with teacache">
<div class="card-body">
<h3 class="card-title">⚡️ Phantom Speed</h3>
<p class="card-text">Teacache slashes ~40% off generation time (~12–15s/frame on RTX 3060).</p>
</div>
</div>
</div>
<div class="col">
<div class="card bg-ghost-card h-100" data-bs-toggle="tooltip" title="Optimized for modest hardware">
<div class="card-body">
<h3 class="card-title">🛠️ Laptop Domination</h3>
<p class="card-text">13B models haunt GPUs with ≥6GB VRAM, tuned for RTX 3060 and budget rigs.</p>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- Optimizations Section -->
<section id="optimizations" class="py-5 bg-light">
<div class="container">
<h2 class="text-center mb-5 animate__animated animate__fadeIn">🧙♂️ Ghostai1’s Math Sorcery</h2>
<p class="lead text-center text-dark mb-4">GhostPack’s SDK is a spectral masterpiece, conjured with ghostai1’s revolutionary math optimizations to haunt any laptop with 8GB RAM.</p>
<!-- Tabs for Optimization Categories -->
<ul class="nav nav-tabs justify-content-center mb-4" id="optTab" role="tablist">
<li class="nav-item" role="presentation">
<button class="nav-link active" id="speed-tab" data-bs-toggle="tab" data-bs-target="#speed" type="button" role="tab" aria-controls="speed" aria-selected="true">⚡️ Speed</button>
</li>
<li class="nav-item" role="presentation">
<button class="nav-link" id="memory-tab" data-bs-toggle="tab" data-bs-target="#memory" type="button" role="tab" aria-controls="memory" aria-selected="false">🔮 Memory</button>
</li>
<li class="nav-item" role="presentation">
<button class="nav-link" id="compute-tab" data-bs-toggle="tab" data-bs-target="#compute" type="button" role="tab" aria-controls="compute" aria-selected="false">🧬 Compute</button>
</li>
</ul>
<div class="tab-content" id="optTabContent">
<!-- Speed Tab -->
<div class="tab-pane fade show active" id="speed" role="tabpanel" aria-labelledby="speed-tab">
<div class="row row-cols-1 row-cols-md-3 g-4 mb-4">
<div class="col">
<div class="card bg-ghost-card text-white h-100" data-bs-toggle="modal" data-bs-target="#teacacheModal">
<div class="card-body text-center">
<h3 class="card-title">🔮 Teacache</h3>
<p class="card-text">Caches diffusion states, slashing ~40% off frame time.</p>
<p><strong>Boost: ~40%</strong><br>Stat: ~12s/frame<br>Math: \( T_{\text{total}} \approx 0.6 \cdot T_{\text{base}} \)</p>
</div>
</div>
</div>
<div class="col">
<div class="card bg-ghost-card text-white h-100" data-bs-toggle="modal" data-bs-target="#sageModal">
<div class="card-body text-center">
<h3 class="card-title">🧙♂️ Sage-Attention</h3>
<p class="card-text">Streamlines attention layers for ~5–10% speed-up.</p>
<p><strong>Boost: ~5–10%</strong><br>Stat: ~1–2s/frame<br>Math: \( T_{\text{attn}} \approx 0.9 \cdot T_{\text{base_attn}} \)</p>
</div>
</div>
</div>
<div class="col">
<div class="card bg-ghost-card text-white h-100" data-bs-toggle="modal" data-bs-target="#cudaModal">
<div class="card-body text-center">
<h3 class="card-title">⚡ CUDA Tweaks</h3>
<p class="card-text">Optimized memory allocation for ~10–15% latency cut.</p>
<p><strong>Boost: ~10–15%</strong><br>Stat: ~10–15% faster<br>Math: \( L_{\text{CUDA}} \approx 0.85 \cdot L_{\text{base}} \)</p>
</div>
</div>
</div>
</div>
</div>
<!-- Memory Tab -->
<div class="tab-pane fade" id="memory" role="tabpanel" aria-labelledby="memory-tab">
<div class="row row-cols-1 row-cols-md-2 g-4 mb-4">
<div class="col">
<div class="card bg-ghost-card text-white h-100" data-bs-toggle="modal" data-bs-target="#contextModal">
<div class="card-body text-center">
<h3 class="card-title">🧬 Context Packing</h3>
<p class="card-text">Compresses contexts, saving ~50% VRAM.</p>
<p><strong>Boost: ~50%</strong><br>Stat: ~2–3GB saved<br>Math: \( M_{\text{VRAM}} \propto O(1) \)</p>
</div>
</div>
</div>
<div class="col">
<div class="card bg-ghost-card text-white h-100" data-bs-toggle="modal" data-bs-target="#tcmallocModal">
<div class="card-body text-center">
<h3 class="card-title">💾 tcmalloc</h3>
<p class="card-text">Cuts memory overhead by ~5–20%, easing CPU load.</p>
<p><strong>Boost: ~5–20%</strong><br>Stat: ~15% CPU relief<br>Math: \( O_{\text{mem}} \approx 0.8 \cdot O_{\text{glibc}} \)</p>
</div>
</div>
</div>
</div>
</div>
<!-- Compute Tab -->
<div class="tab-pane fade" id="compute" role="tabpanel" aria-labelledby="compute-tab">
<div class="row row-cols-1 row-cols-md-1 g-4 mb-4">
<div class="col">
<div class="card bg-ghost-card text-white h-100" data-bs-toggle="modal" data-bs-target="#batchingModal">
<div class="card-body text-center">
<h3 class="card-title">⚡ Dynamic Batching</h3>
<p class="card-text">Adapts batches for ~30–50% throughput gain.</p>
<p><strong>Boost: ~30–50%</strong><br>Stat: ~1.5x FPS<br>Math: \( \text{Throughput} \propto B \cdot \text{FPS}_{\text{base}} \)</p>
</div>
</div>
</div>
</div>
</div>
</div>
<!-- Optimization Breakdown -->
<div class="row">
<div class="col-md-12">
<h3 class="mb-3 text-white">Optimization Breakdown</h3>
<ul class="text-white">
<li><strong>🔮 Compressed Context Packing</strong>: Collapses frame contexts into a fixed-size matrix, slashing VRAM by ~50% (\( M_{\text{VRAM}} \propto O(1) \)), enabling epic 60s videos on 8GB RAM systems like GTX 1650.</li>
<li><strong>🧬 Dynamic Batching</strong>: Adapts frame batches (2–4), boosting throughput by ~30–50% (\( \text{Throughput} \propto B \)), ideal for modest GPUs like RTX 3050.</li>
<li><strong>⚡️ Teacache Efficiency</strong>: Caches diffusion states, cutting ~40% off compute time (\( T_{\text{total}} \approx 0.6T_{\text{base}} \)), hitting ~10–15s/frame on RTX 3060.</li>
<li><strong>🧙♂️ Sage-Attention</strong>: Streamlines attention layers, saving ~5–10% time (\( T_{\text{attn}} \approx 0.9T_{\text{base_attn}} \)), enhancing low-VRAM performance.</li>
<li><strong>💾 tcmalloc</strong>: Reduces memory overhead by ~5–20% (\( O_{\text{mem}} \approx 0.8O_{\text{glibc}} \)), easing CPU load by ~15% for fluid operation.</li>
<li><strong>⚡ CUDA Tweaks</strong>: Cuts latency by ~10–15% (\( L_{\text{CUDA}} \approx 0.85L_{\text{base}} \)) with optimized memory allocation, maximizing GPU efficiency.</li>
</ul>
</div>
</div>
<!-- Speed Chart -->
<div class="row mt-4">
<div class="col-md-12">
<h3 class="text-center text-white mb-3">Speed Across GPUs 📊</h3>
<div class="card bg-ghost-card">
<div class="card-body">
<canvas id="speedChart"></canvas>
</div>
</div>
</div>
</div>
<!-- VRAM Requirements Table -->
<div class="row mt-4">
<div class="col-md-12">
<h3 class="text-center text-white mb-3">VRAM Requirements 🖥️</h3>
<div class="table-responsive">
<table class="table table-dark table-bordered">
<thead>
<tr>
<th>GPU</th>
<th>VRAM</th>
<th>Performance</th>
<th>Notes</th>
</tr>
</thead>
<tbody>
<tr>
<td>GTX 1650</td>
<td>6GB</td>
<td>~18–25s/frame</td>
<td>Minimum spec, teacache recommended.</td>
</tr>
<tr>
<td>RTX 3050</td>
<td>8GB</td>
<td>~15–20s/frame</td>
<td>Balanced, supports batch size 2.</td>
</tr>
<tr>
<td>RTX 3060</td>
<td>12GB</td>
<td>~10–15s/frame</td>
<td>Optimal, batch size 2–4, full features.</td>
</tr>
<tr>
<td>RTX 4090</td>
<td>24GB</td>
<td>~1.5–2.5s/frame</td>
<td>High-end, max batch size, no limits.</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
</section>
<!-- Future Features Section -->
<section id="future" class="py-5 bg-dark text-white">
<div class="container">
<h2 class="text-center mb-5 animate__animated animate__fadeIn">🌌 Future Spectral Phantoms</h2>
<p class="lead text-center">GhostPack is brewing epic upgrades to haunt the AI realm:</p>
<div class="row row-cols-1 row-cols-md-2 g-4">
<div class="col">
<div class="card bg-ghost-card h-100">
<div class="card-body">
<h3 class="card-title">🗣️ Voice Generation</h3>
<p class="card-text">Soon: AI-driven voice synthesis to narrate videos with ghostly tones, integrated into ghostgradio.py.</p>
</div>
</div>
</div>
<div class="col">
<div class="card bg-ghost-card h-100">
<div class="card-body">
<h3 class="card-title">🖼️ AI Images</h3>
<p class="card-text">Future: Generate spectral starting frames with AI-crafted images for cinematic video pipelines.</p>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- Installation Section -->
<section id="installation" class="py-5 bg-light">
<div class="container">
<h2 class="text-center mb-5 animate__animated animate__fadeIn">🛠️ Summon the Code</h2>
<p class="text-center lead text-dark">Unleash GhostPack from the GitHub repo. Requires >30GB disk space.</p>
<div class="row row-cols-1 row-cols-md-3 g-4">
<div class="col">
<h3>🐧 Ubuntu</h3>
<pre><code class="code-block">git clone https://github.com/ghostai1/GhostPack
cd GhostPack
chmod +x install_ubuntu.sh
./install_ubuntu.sh</code></pre>
<p class="text-dark">NVIDIA GPU, 8GB RAM, Python 3.10, CUDA 12.6.</p>
</div>
<div class="col">
<h3>🪟 Windows</h3>
<pre><code class="code-block">git clone https://github.com/ghostai1/GhostPack
cd GhostPack
install.bat</code></pre>
<p class="text-dark">Auto-downloads models (>30GB).</p>
</div>
<div class="col">
<h3>🍎 macOS</h3>
<pre><code class="code-block">git clone https://github.com/ghostai1/GhostPack
cd GhostPack
chmod +x install_macos.sh
./install_macos.sh</code></pre>
<p class="text-dark">M1/M2 support (slower).</p>
</div>
</div>
</div>
</section>
<!-- Usage Section -->
<section id="usage" class="py-5 bg-dark text-white">
<div class="container">
<h2 class="text-center mb-5 animate__animated animate__fadeIn">📹 Weave Ghostly Videos</h2>
<ol>
<li><strong>Launch Phantom GUI</strong>:
<pre><code class="code-block">source ~/ghostpack_venv/venv/bin/activate
cd ~/ghostpack_venv
python ghostgradio.py --port 5666 --server 0.0.0.0</code></pre>
</li>
<li><strong>Craft Spells</strong>:
<ul>
<li>Upload an image.</li>
<li>Prompt: “A spectral figure glides through a neon-lit city.”</li>
<li>Enable teacache (⚡️ speed).</li>
<li>Set 15fps, 5s video (~75 frames).</li>
</ul>
</li>
<li><strong>Summon Spirits</strong>: Run <code>nvidia-smi</code> (~80–100% GPU).</li>
</ol>
</div>
</section>
<!-- Model Card Section -->
<section id="model" class="py-5 bg-light">
<div class="container">
<h2 class="text-center mb-5 animate__animated animate__fadeIn">Spectral Grimoire</h2>
<ul class="text-dark">
<li><strong>Model</strong>: GhostPack-F1 (13B parameters).</li>
<li><strong>Repo</strong>: <a href="https://huggingface.co/spaces/ghostai1/GhostPack" target="_blank">Hugging Face Spaces</a></li>
<li><strong>Files</strong>: >30GB, stored in <code>models/</code> with Git LFS.</li>
<li><strong>License</strong>: Apache-2.0.</li>
</ul>
</div>
</section>
<!-- Footer -->
<footer class="bg-ghost-black text-white text-center py-4">
<p>👻 GhostPack by ghostai1 | <a href="https://github.com/ghostai1/GhostPack" target="_blank">GitHub</a> | <a href="https://huggingface.co/spaces/ghostai1/GhostPack" target="_blank">Hugging Face</a> | Apache-2.0 License</p>
<p>Forged in 😈 hellfire with ⚡️ to haunt video generation forever!</p>
</footer>
<!-- Modals -->
<div class="modal fade" id="teacacheModal" tabindex="-1" aria-labelledby="teacacheModalLabel" aria-hidden="true">
<div class="modal-dialog modal-lg">
<div class="modal-content bg-ghost-card text-white">
<div class="modal-header">
<h5 class="modal-title" id="teacacheModalLabel">🔮 Teacache</h5>
<button type="button" class="btn-close btn-close-white" data-bs-dismiss="modal" aria-label="Close"></button>
</div>
<div class="modal-body">
<p>Teacache caches intermediate diffusion states, reducing redundant computations by ~30–40%. This slashes frame generation time by ~40%, achieving ~12s/frame on RTX 3060.</p>
<p><strong>Math</strong>: \( T_{\text{total}} \approx 0.6 \cdot T_{\text{base}} \), where \( T_{\text{base}} \) is the baseline frame time.</p>
</div>
</div>
</div>
</div>
<div class="modal fade" id="contextModal" tabindex="-1" aria-labelledby="contextModalLabel" aria-hidden="true">
<div class="modal-dialog modal-lg">
<div class="modal-content bg-ghost-card text-white">
<div class="modal-header">
<h5 class="modal-title" id="contextModalLabel">🧬 Context Packing</h5>
<button type="button" class="btn-close btn-close-white" data-bs-dismiss="modal" aria-label="Close"></button>
</div>
<div class="modal-body">
<p>Compresses frame contexts to a fixed-size matrix, saving ~50% VRAM (~2–3GB for 60s videos). Enables long-form content on 6GB VRAM GPUs.</p>
<p><strong>Math</strong>: \( M_{\text{VRAM}} \propto O(1) \), unlike linear scaling \( O(n) \).</p>
</div>
</div>
</div>
</div>
<div class="modal fade" id="batchingModal" tabindex="-1" aria-labelledby="batchingModalLabel" aria-hidden="true">
<div class="modal-dialog modal-lg">
<div class="modal-content bg-ghost-card text-white">
<div class="modal-header">
<h5 class="modal-title" id="batchingModalLabel">⚡ Dynamic Batching</h5>
<button type="button" class="btn-close btn-close-white" data-bs-dismiss="modal" aria-label="Close"></button>
</div>
<div class="modal-body">
<p>Adapts batch sizes (2–4 frames), boosting throughput by ~30–50% (~1.5x FPS). Scales efficiently on modest GPUs like RTX 3050.</p>
<p><strong>Math</strong>: \( \text{Throughput} \propto B \cdot \text{FPS}_{\text{base}} \), where \( B \) is batch size.</p>
</div>
</div>
</div>
</div>
<div class="modal fade" id="sageModal" tabindex="-1" aria-labelledby="sageModalLabel" aria-hidden="true">
<div class="modal-dialog modal-lg">
<div class="modal-content bg-ghost-card text-white">
<div class="modal-header">
<h5 class="modal-title" id="sageModalLabel">🧙♂️ Sage-Attention</h5>
<button type="button" class="btn-close btn-close-white" data-bs-dismiss="modal" aria-label="Close"></button>
</div>
<div class="modal-body">
<p>Optimizes attention layers, reducing computation time by ~5–10% (~1–2s/frame). Enhances performance on low-VRAM GPUs.</p>
<p><strong>Math</strong>: \( T_{\text{attn}} \approx 0.9 \cdot T_{\text{base_attn}} \).</p>
</div>
</div>
</div>
</div>
<div class="modal fade" id="tcmallocModal" tabindex="-1" aria-labelledby="tcmallocModalLabel" aria-hidden="true">
<div class="modal-dialog modal-lg">
<div class="modal-content bg-ghost-card text-white">
<div class="modal-header">
<h5 class="modal-title" id="tcmallocModalLabel">💾 tcmalloc</h5>
<button type="button" class="btn-close btn-close-white" data-bs-dismiss="modal" aria-label="Close"></button>
</div>
<div class="modal-body">
<p>Reduces memory allocation overhead by ~5–20%, easing CPU load by ~15%. Ensures fluid operation on 8GB RAM systems.</p>
<p><strong>Math</strong>: \( O_{\text{mem}} \approx 0.8 \cdot O_{\text{glibc}} \).</p>
</div>
</div>
</div>
</div>
<div class="modal fade" id="cudaModal" tabindex="-1" aria-labelledby="cudaModalLabel" aria-hidden="true">
<div class="modal-dialog modal-lg">
<div class="modal-content bg-ghost-card text-white">
<div class="modal-header">
<h5 class="modal-title" id="cudaModalLabel">⚡ CUDA Tweaks</h5>
<button type="button" class="btn-close btn-close-white" data-bs-dismiss="modal" aria-label="Close"></button>
</div>
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<p>Optimizes CUDA memory allocation, reducing latency by ~10–15%. Maximizes GPU efficiency on RTX 3060 and beyond.</p>
<p><strong>Math</strong>: \( L_{\text{CUDA}} \approx 0.85 \cdot L_{\text{base}} \).</p>
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