GGUF quantization of junwatu/resep-ID-gemma-4-E2B-it, a fine-tune of google/gemma-4-e2b-it for Indonesian recipe generation. This is the portable, runs-on-your-laptop version. Use it with llama.cpp, Ollama, LM Studio, or any GGUF-compatible runtime. 1. Search for junwatu/resep-ID-gemma-4-E2B-it-gguf in the model browser 2. Download Q4KM 3. Important: in the inference settings, set Repeat penalty norepeatngramsize = 6`** — without this, the model can get stuck in repetition loops on long recipes Give it an Indonesian recipe title, get back a structured Bahan: … Langkah: … recipe in natural Bahasa Indonesia. Trained on ~66K real home-cook recipes. See the base model card for full details on what it does well, what it doesn’t, and the rubric eval results vs stock Gemma 4. norepeatngramsize = 6`**. Without it, the model can fall into repetition loops on long recipes (like rendang or tengkleng with many spices). With it, generations terminate cleanly. Q4KM typically loses ~3-5% quality vs the full-precision model. For recipe generation that’s largely imperceptible — same dish identity, same format, same step coherence. The full bf16 original lives at junwatu/resep-ID-gemma-4-E2B-it…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: junwatu
Теги: gguf, quantized, recipes, indonesian, gemma-4, llama.cpp, id, endpoints_compatible
Лайков: 4 | Загрузок: 0
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
