A fine-tuned Qwen2.5-VL-3B-Instruct model specialized for converting database schema diagrams into structured JSON format. This model dramatically improves upon the base model’s ability to understand and extract information from ER diagrams, database schemas, and other structured database documentation. This model addresses a common pain point in database documentation and migration projects: manually transcribing database schema diagrams is time-consuming and error-prone. While the base Qwen2.5-VL model struggled with structured diagram interpretation (often missing tables, incorrectly identifying relationships, or producing malformed outputs), this fine-tuned version shows significant improvements across all metrics. The model uses LoRA (Low-Rank Adaptation) for parameter-efficient fine-tuning, targeting attention layers for optimal performance while maintaining efficiency. — Developed by: David Nguyen — Model type: Vision-Language Model (Fine-tuned) — Language(s): English — License: Same as base model (Qwen2.5-VL-3B-Instruct) — Finetuned from model: Qwen/Qwen2.5-VL-3B-Instruct — Repository: GitHub Repository — Base Model: Qwen/Qwen2.5-VL-3B-Instruct The fine-tuned model shows…
Модальности:
Генерация текста Анализ изображений
Области применения:
Диалог / чат Текст в SQL
Задача: Генерация текста
Автор: zodiac2525
Теги: peft, qwen2_5_vl, image-text-to-text, lora, image-to-text, conversational, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 9
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
