A Q8_0 quantized GGUF of Qwen3.5-0.8B fine-tuned on 685 distilled question/answer pairs harvested from the Chipotle support chatbot (Pepper). This is a small persona model. It was trained as a personal project to see how far a 0.8B model could go with ~1M tokens of support-bot Q&A, adversarial red-teaming, and instruction-format training. — ~685 cleaned Q&A pairs distilled from the Chipotle support chatbot — Adversarial red-team rephrasings (edge cases, out-of-scope deflection) — Identity / persona pairs Known junk patterns (self-referential Q&A, accordion artifacts) were programmatically filtered out of the raw harvest. The model answers in the persona of a fast-food support chatbot. It: — Handles common questions (menu, hours, orders, rewards) with ground-truth answers from the harvest — Deflects out-of-scope questions with canned boundary replies — Has been red-teamed against over-claiming and adversarial rephrasings — May still hallucinate or get details wrong — it’s a 0.8B, treat it accordingly Drop the GGUF in your models folder and load it — the Qwen chat template is baked into the file. it thinks the quant is nonexistent tho lmao This is an unofficial, fan-made project. It…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: bnjlebron
Теги: gguf, llama-cpp, qwen3.5, chat, distilled, chipotle, en, endpoints_compatible
Лайков: 3 | Загрузок: 43
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
