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ad-generator

Here are 10 public repositories matching this topic...

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...

  • Updated Nov 27, 2024
  • Python

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...

  • Updated Jan 16, 2025
  • JavaScript

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...

  • Updated Nov 27, 2024
  • PHP

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...

  • Updated Nov 27, 2024
  • Ruby

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...

  • Updated Nov 27, 2024
  • Go

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.

  • Updated Feb 4, 2024
  • Jupyter Notebook

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