This is the Q4KM quantization (~2.4 GB) of CogEvol-4B, built with llama.cpp. It runs a full learning-environment generation model on a laptop, fully offline. CogEvol-4B is a post-trained model for Learning Environment Generation (LEG): given a natural-language course brief, it generates complete, usable learning artifacts in a single pass — a structured-JSON slide page, or a self-contained interactive HTML page that runs directly in the browser. Full-precision weights, deployment guide, and tech report links live in the main model card and the GitHub repository. Generated slides with this Q4 checkpoint were compared side-by-side against the BF16 model (same prompts, same settings) on 5 production briefs: element structure matched (4/5 identical element counts, 1 near-match from a BF16-side truncation artifact), zero rendering corruption, and manual review found the Q4 outputs at parity or better. Rendered comparisons are in examples/ (bf16/ vs q4/). The GitHub repository is the complete, maintained deployment guide — serving script with the validated flags, OpenMAIC app integration, a fully-offline walkthrough, evaluation scripts and a troubleshooting table. The short version: -…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: CogEvol
Теги: gguf, q4_k_m, llama.cpp, quantized, learning-environment-generation, slide-generation, interactive-html, education
Лайков: 3 | Загрузок: 150
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
