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<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Polyglot NLP | Transfer Learning for Low-Resource Languages</title>
    <script src="https://cdn.tailwindcss.com"></script>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
    <style>
        .gradient-bg {
            background: linear-gradient(135deg, #6B73FF 0%, #000DFF 50%, #00D4FF 100%);
        }
        .language-card:hover {
            transform: translateY(-5px);
            box-shadow: 0 10px 25px rgba(0, 0, 0, 0.1);
        }
        .model-visualization {
            background: linear-gradient(45deg, #f3f4f6 0%, #e5e7eb 100%);
        }
        .typing-demo {
            width: 22ch;
            animation: typing 2s steps(22), blink .5s step-end infinite alternate;
            white-space: nowrap;
            overflow: hidden;
            border-right: 3px solid;
            font-family: monospace;
        }
        @keyframes typing {
            from { width: 0 }
        }
        @keyframes blink {
            50% { border-color: transparent }
        }
    </style>
</head>
<body class="font-sans antialiased text-gray-800">
    <!-- Navigation -->
    <nav class="bg-white shadow-lg sticky top-0 z-50">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
            <div class="flex justify-between h-16">
                <div class="flex items-center">
                    <div class="flex-shrink-0 flex items-center">
                        <i class="fas fa-language text-3xl text-blue-600 mr-2"></i>
                        <span class="text-xl font-bold text-gray-900">PolyglotNLP</span>
                    </div>
                </div>
                <div class="hidden md:ml-6 md:flex md:items-center md:space-x-8">
                    <a href="#home" class="text-gray-900 hover:text-blue-600 px-3 py-2 text-sm font-medium">Home</a>
                    <a href="#features" class="text-gray-900 hover:text-blue-600 px-3 py-2 text-sm font-medium">Features</a>
                    <a href="#demo" class="text-gray-900 hover:text-blue-600 px-3 py-2 text-sm font-medium">Demo</a>
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                    <a href="#contact" class="bg-blue-600 text-white px-4 py-2 rounded-md text-sm font-medium hover:bg-blue-700 transition">Get Started</a>
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                        <span class="sr-only">Open main menu</span>
                        <i class="fas fa-bars"></i>
                    </button>
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        </div>

        <!-- Mobile menu -->
        <div class="hidden md:hidden" id="mobile-menu">
            <div class="pt-2 pb-3 space-y-1">
                <a href="#home" class="bg-blue-50 border-blue-500 text-blue-600 block pl-3 pr-4 py-2 border-l-4 text-base font-medium">Home</a>
                <a href="#features" class="border-transparent text-gray-600 hover:bg-gray-50 hover:border-gray-300 hover:text-gray-800 block pl-3 pr-4 py-2 border-l-4 text-base font-medium">Features</a>
                <a href="#demo" class="border-transparent text-gray-600 hover:bg-gray-50 hover:border-gray-300 hover:text-gray-800 block pl-3 pr-4 py-2 border-l-4 text-base font-medium">Demo</a>
                <a href="#about" class="border-transparent text-gray-600 hover:bg-gray-50 hover:border-gray-300 hover:text-gray-800 block pl-3 pr-4 py-2 border-l-4 text-base font-medium">About</a>
                <a href="#contact" class="block w-full px-4 py-2 text-center text-white bg-blue-600 rounded-md hover:bg-blue-700 transition">Get Started</a>
            </div>
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    </nav>

    <!-- Hero Section -->
    <section id="home" class="gradient-bg text-white py-20">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
            <div class="lg:grid lg:grid-cols-2 lg:gap-8 items-center">
                <div class="mb-12 lg:mb-0">
                    <h1 class="text-4xl md:text-5xl font-bold mb-6 leading-tight">
                        Breaking Language Barriers with <span class="typing-demo">Transfer Learning</span>
                    </h1>
                    <p class="text-xl mb-8 text-blue-100">
                        Empowering low-resource languages through advanced NLP techniques. Our transfer learning models bring high-quality language processing to underserved communities.
                    </p>
                    <div class="flex flex-col sm:flex-row space-y-4 sm:space-y-0 sm:space-x-4">
                        <a href="#demo" class="bg-white text-blue-600 hover:bg-gray-100 px-6 py-3 rounded-lg text-lg font-semibold text-center transition duration-300">
                            Try Our Demo
                        </a>
                        <a href="#about" class="border-2 border-white text-white hover:bg-white hover:text-blue-600 px-6 py-3 rounded-lg text-lg font-semibold text-center transition duration-300">
                            Learn More
                        </a>
                    </div>
                </div>
                <div class="relative">
                    <div class="bg-white/10 backdrop-blur-md rounded-2xl p-6 border border-white/20">
                        <div class="flex items-center mb-4">
                            <div class="w-3 h-3 rounded-full bg-red-500 mr-2"></div>
                            <div class="w-3 h-3 rounded-full bg-yellow-500 mr-2"></div>
                            <div class="w-3 h-3 rounded-full bg-green-500"></div>
                        </div>
                        <div class="bg-black/30 rounded-lg p-4 font-mono text-sm overflow-auto h-64">
                            <p class="text-green-400"># Initialize base model (mBERT)</p>
                            <p class="text-green-400">base_model = AutoModel.from_pretrained('bert-base-multilingual-cased')</p>
                            <br>
                            <p class="text-green-400"># Add task-specific layers</p>
                            <p class="text-green-400">class PolyglotModel(nn.Module):</p>
                            <p class="text-green-400 ml-4">def __init__(self, base_model, num_languages):</p>
                            <p class="text-green-400 ml-8">super().__init__()</p>
                            <p class="text-green-400 ml-8">self.base = base_model</p>
                            <p class="text-green-400 ml-8">self.classifier = nn.Linear(768, num_languages)</p>
                            <br>
                            <p class="text-green-400 ml-4">def forward(self, input_ids, attention_mask):</p>
                            <p class="text-green-400 ml-8">outputs = self.base(input_ids, attention_mask)</p>
                            <p class="text-green-400 ml-8">pooled = outputs.last_hidden_state[:, 0, :]</p>
                            <p class="text-green-400 ml-8">return self.classifier(pooled)</p>
                            <br>
                            <p class="text-green-400"># Train with low-resource data</p>
                            <p class="text-green-400">train_model(low_resource_data, epochs=5, lr=2e-5)</p>
                        </div>
                    </div>
                    <div class="absolute -bottom-6 -right-6 bg-yellow-400 text-gray-900 px-4 py-2 rounded-lg shadow-lg font-bold">
                        Transfer Learning in Action
                    </div>
                </div>
            </div>
        </div>
    </section>

    <!-- Supported Languages -->
    <section class="py-16 bg-gray-50">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
            <div class="text-center mb-12">
                <h2 class="text-3xl font-bold text-gray-900 mb-4">Supported Low-Resource Languages</h2>
                <p class="text-xl text-gray-600 max-w-3xl mx-auto">
                    We currently support these languages with limited digital resources, helping bridge the digital divide.
                </p>
            </div>
            
            <div class="grid grid-cols-2 md:grid-cols-4 lg:grid-cols-6 gap-6">
                <!-- Language Cards -->
                <div class="language-card bg-white p-6 rounded-xl shadow-md transition duration-300 flex flex-col items-center">
                    <div class="w-16 h-16 bg-blue-100 rounded-full flex items-center justify-center mb-4">
                        <span class="text-2xl">🇮🇳</span>
                    </div>
                    <h3 class="font-bold text-lg mb-1">Nepali</h3>
                    <p class="text-gray-600 text-sm text-center">~30M speakers</p>
                    <div class="mt-3 w-full bg-gray-200 rounded-full h-2">
                        <div class="bg-blue-600 h-2 rounded-full" style="width: 45%"></div>
                    </div>
                    <span class="text-xs mt-1 text-gray-500">45% coverage</span>
                </div>
                
                <div class="language-card bg-white p-6 rounded-xl shadow-md transition duration-300 flex flex-col items-center">
                    <div class="w-16 h-16 bg-green-100 rounded-full flex items-center justify-center mb-4">
                        <span class="text-2xl">🇪🇹</span>
                    </div>
                    <h3 class="font-bold text-lg mb-1">Amharic</h3>
                    <p class="text-gray-600 text-sm text-center">~25M speakers</p>
                    <div class="mt-3 w-full bg-gray-200 rounded-full h-2">
                        <div class="bg-green-600 h-2 rounded-full" style="width: 38%"></div>
                    </div>
                    <span class="text-xs mt-1 text-gray-500">38% coverage</span>
                </div>
                
                <div class="language-card bg-white p-6 rounded-xl shadow-md transition duration-300 flex flex-col items-center">
                    <div class="w-16 h-16 bg-purple-100 rounded-full flex items-center justify-center mb-4">
                        <span class="text-2xl">🇰🇪</span>
                    </div>
                    <h3 class="font-bold text-lg mb-1">Swahili</h3>
                    <p class="text-gray-600 text-sm text-center">~16M speakers</p>
                    <div class="mt-3 w-full bg-gray-200 rounded-full h-2">
                        <div class="bg-purple-600 h-2 rounded-full" style="width: 65%"></div>
                    </div>
                    <span class="text-xs mt-1 text-gray-500">65% coverage</span>
                </div>
                
                <div class="language-card bg-white p-6 rounded-xl shadow-md transition duration-300 flex flex-col items-center">
                    <div class="w-16 h-16 bg-yellow-100 rounded-full flex items-center justify-center mb-4">
                        <span class="text-2xl">🇲🇲</span>
                    </div>
                    <h3 class="font-bold text-lg mb-1">Burmese</h3>
                    <p class="text-gray-600 text-sm text-center">~33M speakers</p>
                    <div class="mt-3 w-full bg-gray-200 rounded-full h-2">
                        <div class="bg-yellow-600 h-2 rounded-full" style="width: 28%"></div>
                    </div>
                    <span class="text-xs mt-1 text-gray-500">28% coverage</span>
                </div>
                
                <div class="language-card bg-white p-6 rounded-xl shadow-md transition duration-300 flex flex-col items-center">
                    <div class="w-16 h-16 bg-red-100 rounded-full flex items-center justify-center mb-4">
                        <span class="text-2xl">🇮🇳</span>
                    </div>
                    <h3 class="font-bold text-lg mb-1">Odia</h3>
                    <p class="text-gray-600 text-sm text-center">~35M speakers</p>
                    <div class="mt-3 w-full bg-gray-200 rounded-full h-2">
                        <div class="bg-red-600 h-2 rounded-full" style="width: 22%"></div>
                    </div>
                    <span class="text-xs mt-1 text-gray-500">22% coverage</span>
                </div>
                
                <div class="language-card bg-white p-6 rounded-xl shadow-md transition duration-300 flex flex-col items-center">
                    <div class="w-16 h-16 bg-indigo-100 rounded-full flex items-center justify-center mb-4">
                        <span class="text-2xl">🇵🇰</span>
                    </div>
                    <h3 class="font-bold text-lg mb-1">Sindhi</h3>
                    <p class="text-gray-600 text-sm text-center">~30M speakers</p>
                    <div class="mt-3 w-full bg-gray-200 rounded-full h-2">
                        <div class="bg-indigo-600 h-2 rounded-full" style="width: 18%"></div>
                    </div>
                    <span class="text-xs mt-1 text-gray-500">18% coverage</span>
                </div>
            </div>
            
            <div class="mt-12 text-center">
                <a href="#" class="inline-flex items-center text-blue-600 hover:text-blue-800 font-medium">
                    Request a language <i class="fas fa-arrow-right ml-2"></i>
                </a>
            </div>
        </div>
    </section>

    <!-- Features Section -->
    <section id="features" class="py-16 bg-white">
        <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
            <div class="text-center mb-16">
                <h2 class="text-3xl font-bold text-gray-900 mb-4">Our Transfer Learning Approach</h2>
                <p class="text-xl text-gray-600 max-w-3xl mx-auto">
                    Leveraging state-of-the-art techniques to bring NLP to languages with limited digital resources.
                </p>
            </div>
            
            <div class="grid md:grid-cols-3 gap-8">
                <!-- Feature 1 -->
                <div class="bg-gray-50 p-8 rounded-xl">
                    <div class="w-14 h-14 bg-blue-100 rounded-lg flex items-center justify-center mb-6">
                        <i class="fas fa-project-diagram text-blue-600 text-2xl"></i>
                    </div>
                    <h3 class="text-xl font-bold mb-3">Multilingual Base Models</h3>
                    <p class="text-gray-600 mb-4">
                        We use pretrained multilingual models like mBERT and XLM-R as our foundation, then fine-tune them for specific low-resource languages.
                    </p>
                    <ul class="space-y-2">
                        <li class="flex items-start">
                            <i class="fas fa-check text-green-500 mt-1 mr-2"></i>
                            <span>Leverages cross-lingual transfer</span>
                        </li>
                        <li class="flex items-start">
                            <i class="fas fa-check text-green-500 mt-1 mr-2"></i>
                            <span>Requires minimal target language data</span>
                        </li>
                    </ul>
                </div>
                
                <!-- Feature 2 -->
                <div class="bg-gray-50 p-8 rounded-xl">
                    <div class="w-14 h-14 bg-purple-100 rounded-lg flex items-center justify-center mb-6">
                        <i class="fas fa-layer-group text-purple-600 text-2xl"></i>
                    </div>
                    <h3 class="text-xl font-bold mb-3">Adaptive Fine-Tuning</h3>
                    <p class="text-gray-600 mb-4">
                        Our progressive unfreezing technique carefully adapts the model layers to preserve valuable multilingual knowledge while specializing for target languages.
                    </p>
                    <ul class="space-y-2">
                        <li class="flex items-start">
                            <i class="fas fa-check text-green-500 mt-1 mr-2"></i>
                            <span>Preserves multilingual capabilities</span>
                        </li>
                        <li class="flex items-start">
                            <i class="fas fa-check text-green-500 mt-1 mr-2"></i>
                            <span>Optimizes for low-resource scenarios</span>
                        </li>
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                    <h3 class="text-xl font-bold mb-3">Task-Specific Heads</h3>
                    <p class="text-gray-600 mb-4">
                        We add lightweight task-specific layers on top of the multilingual base, enabling efficient adaptation for various NLP tasks with minimal data.
                    </p>
                    <ul class="space-y-2">
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                            <span>Supports multiple NLP tasks</span>
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                            <span>Reduces catastrophic forgetting</span>
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                <h3 class="text-2xl font-bold mb-6 text-center">Our Transfer Learning Architecture</h3>
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                        <!-- Model layers visualization -->
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                            <!-- Input -->
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                                Input Text (Low-Resource Language)
                            </div>
                            
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                                    Shared Vocabulary
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                            <!-- Base Model -->
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                                <div class="text-center mb-2 text-sm font-medium">Multilingual Base Model (Frozen Initial Layers)</div>
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                                <div class="text-center mb-2 text-sm font-medium">Adaptive Fine-Tuned Layers</div>
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                                    Trained on Target Data
                                </div>
                            </div>
                            
                            <!-- Output -->
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                                Task Output (e.g., Translation, Sentiment, etc.)
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                <h2 class="text-3xl font-bold text-gray-900 mb-4">Try Our Polyglot NLP Demo</h2>
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                    Experience how transfer learning enables NLP for low-resource languages.
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                        <h3 class="text-xl font-bold mb-6">Input Text</h3>
                        
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                            <label class="block text-sm font-medium text-gray-700 mb-2">Select Language</label>
                            <select id="language-select" class="w-full px-4 py-2 border border-gray-300 rounded-lg focus:ring-blue-500 focus:border-blue-500">
                                <option value="nepali">Nepali (नेपाली)</option>
                                <option value="amharic">Amharic (አማርኛ)</option>
                                <option value="swahili">Swahili (Kiswahili)</option>
                                <option value="burmese">Burmese (မြန်မာဘာသာ)</option>
                            </select>
                        </div>
                        
                        <div class="mb-6">
                            <label class="block text-sm font-medium text-gray-700 mb-2">Select Task</label>
                            <select id="task-select" class="w-full px-4 py-2 border border-gray-300 rounded-lg focus:ring-blue-500 focus:border-blue-500">
                                <option value="sentiment">Sentiment Analysis</option>
                                <option value="translation">Translation to English</option>
                                <option value="ner">Named Entity Recognition</option>
                            </select>
                        </div>
                        
                        <div>
                            <label class="block text-sm font-medium text-gray-700 mb-2">Enter Text</label>
                            <textarea id="input-text" class="w-full px-4 py-3 border border-gray-300 rounded-lg focus:ring-blue-500 focus:border-blue-500 h-32" placeholder="Type or paste text here..."></textarea>
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                            <i class="fas fa-cogs mr-2"></i> Process Text
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                    <!-- Output Section -->
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                        <h3 class="text-xl font-bold mb-6">Results</h3>
                        
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                            <div class="inline-block animate-spin rounded-full h-12 w-12 border-t-2 border-b-2 border-blue-500 mb-4"></div>
                            <p class="text-gray-600">Processing your text with our transfer learning model...</p>
                        </div>
                        
                        <div id="results" class="hidden">
                            <div class="mb-6">
                                <h4 class="font-medium text-gray-700 mb-2">Input Language</h4>
                                <div id="input-lang" class="px-4 py-2 bg-gray-100 rounded-lg"></div>
                            </div>
                            
                            <div class="mb-6">
                                <h4 class="font-medium text-gray-700 mb-2">Task Performed</h4>
                                <div id="task-performed" class="px-4 py-2 bg-gray-100 rounded-lg"></div>
                            </div>
                            
                            <div>
                                <h4 class="font-medium text-gray-700 mb-2">Results</h4>
                                <div id="result-output" class="px-4 py-3 bg-gray-100 rounded-lg min-h-32"></div>
                            </div>
                            
                            <div id="confidence" class="mt-4 hidden">
                                <h4 class="font-medium text-gray-700 mb-2">Model Confidence</h4>
                                <div class="w-full bg-gray-200 rounded-full h-2.5">
                                    <div id="confidence-bar" class="bg-blue-600 h-2.5 rounded-full" style="width: 0%"></div>
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                                <p id="confidence-value" class="text-sm text-gray-600 mt-1"></p>
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                        </div>
                        
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                            <i class="fas fa-language text-4xl text-gray-300 mb-4"></i>
                            <h4 class="font-medium text-gray-500 mb-2">No results yet</h4>
                            <p class="text-gray-400">Enter some text and click "Process Text" to see our transfer learning model in action.</p>
                        </div>
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                        <h3 class="text-lg font-medium text-blue-800">About This Demo</h3>
                        <p class="mt-2 text-blue-700">
                            This demo simulates how our transfer learning approach works with low-resource languages. While we can't run actual models in the browser, this shows the interface and expected behavior of our system.
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                    <h2 class="text-3xl font-bold text-gray-900 mb-6">Our Mission: Inclusive NLP</h2>
                    <p class="text-lg text-gray-600 mb-6">
                        Over 3,000 languages are spoken worldwide, yet most NLP research focuses on just a handful of high-resource languages. We're changing that by making NLP accessible to all languages, regardless of available digital resources.
                    </p>
                    <p class="text-lg text-gray-600 mb-8">
                        Our transfer learning techniques allow us to achieve state-of-the-art results with as little as 1% of the data typically required for training NLP models from scratch.
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                                <h3 class="text-lg font-medium text-gray-900">Data Efficiency</h3>
                                <p class="mt-2 text-gray-600">
                                    Achieve 90% of high-resource language performance with just thousands (not millions) of training examples.
                                </p>
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                                <h3 class="text-lg font-medium text-gray-900">Cross-Lingual Transfer</h3>
                                <p class="mt-2 text-gray-600">
                                    Knowledge from related languages boosts performance on truly low-resource languages.
                                </p>
                            </div>
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                <div class="relative">
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                        <h3 class="text-xl font-bold mb-6">Performance Comparison</h3>
                        <p class="text-gray-600 mb-6">
                            Our transfer learning approach outperforms traditional methods for low-resource languages:
                        </p>
                        
                        <div class="space-y-6">
                            <!-- Chart -->
                            <div class="bg-white p-4 rounded-lg border border-gray-200">
                                <div class="flex justify-between mb-2">
                                    <span class="text-sm font-medium text-gray-500">Model</span>
                                    <span class="text-sm font-medium text-gray-500">F1 Score</span>
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                                    <!-- From Scratch -->
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                                        <div class="flex justify-between mb-1">
                                            <span class="text-sm font-medium text-gray-700">From Scratch</span>
                                            <span class="text-sm font-medium text-gray-700">42%</span>
                                        </div>
                                        <div class="w-full bg-gray-200 rounded-full h-2.5">
                                            <div class="bg-red-500 h-2.5 rounded-full" style="width: 42%"></div>
                                        </div>
                                    </div>
                                    
                                    <!-- Standard Fine-Tuning -->
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                                        <div class="flex justify-between mb-1">
                                            <span class="text-sm font-medium text-gray-700">Standard Fine-Tuning</span>
                                            <span class="text-sm font-medium text-gray-700">67%</span>
                                        </div>
                                        <div class="w-full bg-gray-200 rounded-full h-2.5">
                                            <div class="bg-yellow-500 h-2.5 rounded-full" style="width: 67%"></div>
                                        </div>
                                    </div>
                                    
                                    <!-- Our Approach -->
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                                        <div class="flex justify-between mb-1">
                                            <span class="text-sm font-medium text-gray-700">Our Transfer Learning</span>
                                            <span class="text-sm font-medium text-gray-700">83%</span>
                                        </div>
                                        <div class="w-full bg-gray-200 rounded-full h-2.5">
                                            <div class="bg-green-500 h-2.5 rounded-full" style="width: 83%"></div>
                                        </div>
                                    </div>
                                </div>
                                
                                <p class="text-xs text-gray-500 mt-4 italic">Average performance across 5 low-resource languages on NER task</p>
                            </div>
                            
                            <!-- Data Requirements -->
                            <div class="bg-white p-4 rounded-lg border border-gray-200">
                                <h4 class="font-medium mb-3">Data Requirements Comparison</h4>
                                <div class="grid grid-cols-3 gap-4 text-center">
                                    <div>
                                        <div class="text-2xl font-bold text-red-500">1M+</div>
                                        <div class="text-xs text-gray-500">From Scratch</div>
                                    </div>
                                    <div>
                                        <div class="text-2xl font-bold text-yellow-500">100K</div>
                                        <div class="text-xs text-gray-500">Standard FT</div>
                                    </div>
                                    <div>
                                        <div class="text-2xl font-bold text-green-500">10K</div>
                                        <div class="text-xs text-gray-500">Our Approach</div>
                                    </div>
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                            <span class="font-medium">83% average performance</span>
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                        Whether you're a researcher, developer, or language community representative, we'd love to hear from you.
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