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  "path": "/t/need-generative-model-high-quality-description-generation/176230#post_1",
  "publishedAt": "2026-05-26T05:23:49.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "## Problem statement\n\nI am building operator profile descriptions for a local-services marketplace from structured inputs like skill, city, state, rate, and experience. I need descriptions that sound human-written, stay factually correct, and remain diverse across many operator pages.\n\nI tried Hugging Face/open-source local models, Qwen, Phi-3, and free-tier Google API models, but the results are still not satisfactory for production quality. So far, the API-based result was the best, but I want suggestions for a better non-API or hybrid approach for this use case.\n\n**What I tried:** Fixed templates became repetitive at scale and risk near-duplicate quality issues; then I tried a hybrid pipeline where I first extract facts and then rewrite with a model, and I tested local/open models like Qwen and Phi-3 plus free-tier Google API models, but only the API-based output was reasonably good so far.\n\n**What I need suggestions for:** the best approach to generate long 3-paragraph and 5 other types of human-like business descriptions from structured facts, keep facts fixed while improving writing quality, reduce repetition across 10,000+ pages without massive hardcoded templates, and build a feasible SEO-, GEO-, and large-scale programmatic-content pipeline with strong quality control.",
  "title": "Need generative model, high-quality description generation"
}