Open-source implementation of Pomelli project by Google
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Updated
Aug 2, 2026 - TypeScript
Open-source implementation of Pomelli project by Google
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, code generation, and more...
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, code generation, and much more...
A professional-grade text randomizer and ad generator by @AiratTop — perfect for creating unique, human-readable content at scale. Moved to https://random.airat.top
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, code generation, and much more...
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, code generation, and much more...
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, code generation, and much more...
🚀 Turn any product URL into a professional AI-generated video ad using GPT-4, Remotion, and Puppeteer — a full-stack project that automates ad creation in minutes.
Free open-source AI marketing tool and AI ad generator for Google Ads, Meta/Facebook, Instagram, TikTok, LinkedIn, YouTube and X. Open-source alternative to Jasper, AdCreative, Anyword and Copy.ai. 18 AI generators, 11 optimizers, 9 BYOK providers (Claude, GPT, Gemini, Groq, DeepSeek). Browser-only, no backend, no subscription. MIT.
AI-powered video-to-ad content generator. Paste any Instagram Reel, YouTube Short, or Facebook Ad — get adapted scripts, hooks, and captions for your brand. Built with Next.js, Gemini AI, and shadcn/ui.
Amharic RAG Ad Builder is an open-source project that delivers a powerful Retrieval-Augmented Generation (RAG) pipeline tailored for creating engaging Amharic text advertisements on Telegram channels. It leverages advanced language models to generate contextually relevant ads, enhancing advertising strategies for the Ethiopian market.
Client-side text randomizer with synonyms, permutations, unlimited nesting, %rand%, unique output without duplicates, and Text/JSON/CSV output with .txt/.json download. Published at https://random.airat.top
Ad generation via offline LLMs with on-device inference, optionally managed by a self-hosted CMS.
AI-powered ad creative generator for Google Ads, Meta Ads, TikTok Ads, and Taboola — platform-compliant copy in seconds.
Utilizing image-to-text generating machine learning models, the project automates the creation of visually engaging storyboards from ad descriptions. The repo includes data analysis, asset generation, composition, and storyboard construction.
Text classification of Amazon product reviews as positive or negative
Research project for CLEF 2025 Touché Lab on “Advertisements in Retrieval-Augmented Generation.” Covers Subtask 1 (ad generation via RAG pipeline with FAISS, CrossEncoder, Qwen) and Subtask 2 (ad detection using fine-tuned DeBERTa and RoBERTa models). Ranked 2nd and 4th internationally, presented at CLEF 2025 in Madrid.
Generate unique, privacy-first text randomizations fully in-browser with support for synonyms, permutations, and large batch outputs without duplicates.
Provide local JSON formatting, validation, conversion, and sorting with a static, client-side tool that requires no server or backend.
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