A fine-tuned text generation model for query generation from presentation template metadata. This model uses LoRA adapters to efficiently fine-tune Google Gemma-3-4B for generating diverse and relevant search queries as part of the Field-Adaptive Dense Retrieval framework. Finetuned from model: unsloth/gemma-3-4b-it-unsloth-bnb-4bit Paper: Field-Adaptive Dense Retrieval of Structured Documents — Repository: https://github.com/mudasir13cs/hybrid-search — Paper: https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE12352544 — Base Model: https://huggingface.co/unsloth/gemma-3-4b-it-unsloth-bnb-4bit This model is designed for generating search queries from presentation template metadata including titles, descriptions, industries, categories, and tags. It serves as a key component in the Field-Adaptive Dense Retrieval system for structured documents. — Content generation systems — SEO optimization tools — Template recommendation engines — Automated content creation — Field-adaptive search query generation — Dense retrieval systems for structured documents — Query expansion and reformulation — Factual information generation — Medical or legal advice — Harmful content generation -…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: mudasir13cs
Теги: lora, peft, presentation-templates, information-retrieval, gemma, conversational, en, endpoints_compatible
Лайков: 3 | Загрузок: 0
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
