babatdaa's picture
Create a Python code template using Hugging Face Transformers and scikit-learn to build a generative AI model that produces marketing content (e.g., email campaigns or social media posts) for e-commerce businesses. Integrate a predictive component that analyzes user data (e.g., purchase history CSV) to forecast customer preferences and tailor the generated text accordingly. Include fine-tuning on a dataset like GPT-2 or Llama, with evaluation metrics for coherence and accuracy. Make it automation-ready for freelancers charging premium rates, with examples for handling surged demand in personalized experiences. Output the full code, explanations, and sample usage.
d6c8af7 verified
// Shared functionality
document.addEventListener('DOMContentLoaded', () => {
// Scroll animations
const animateOnScroll = () => {
const elements = document.querySelectorAll('.scroll-animate');
elements.forEach(el => {
const elTop = el.getBoundingClientRect().top;
const isVisible = (elTop - window.innerHeight) < -100;
if (isVisible && !el.classList.contains('animate-fade-in')) {
el.classList.add('animate-fade-in');
}
});
};
window.addEventListener('scroll', animateOnScroll);
animateOnScroll(); // Run once on load
// Theme switcher
const themeToggle = document.getElementById('theme-toggle');
if (themeToggle) {
themeToggle.addEventListener('click', () => {
document.documentElement.classList.toggle('dark');
localStorage.setItem('theme', document.documentElement.classList.contains('dark') ? 'dark' : 'light');
});
}
});
// API Client
class AIForgeAPI {
constructor() {
this.baseUrl = 'https://api.aiforge.com/v1';
}
async getTemplates(category) {
const response = await fetch(`${this.baseUrl}/templates?category=${category}`);
return response.json();
}
async createProject(config) {
const response = await fetch(`${this.baseUrl}/projects`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${localStorage.getItem('token')}`
},
body: JSON.stringify(config)
});
return response.json();
}
}