EXPERIMENTAL MODEL, NOT FINAL, IT HAS SOME ISSUES, BUT IT’S REALLY COOL WHEN IT WORKS The biggest change from my previous AEZAKMI models is that this one is much much less likely to refuse completing request! Yi-34B 200K base model fine-tuned on RAWrr v1 dataset via DPO and then fine-tuned on AEZAKMI v2 dataset via SFT. DPO training took around 6 hours, SFT took around 18 hours. I used unsloth for both stages. It’s like airoboros but with less gptslop, no refusals and less typical language used by RLHFed OpenAI models. Say goodbye to «It’s important to remember»! Prompt format is standard chatml. Don’t expect it to be good at math, riddles or be crazy smart. My end goal with AEZAKMI is to create a cozy free chatbot. Base model used for fine-tuning was 200k context Yi-34B-Llama model shared by larryvrh. Training was done with maxpositionembeddings set at 4096. Then it was reverted back to 200K after applying LoRA. I recommend using ChatML format, as this was used during fine-tune. Here’s a prompt format you should use, you can set a different system message, model seems to respect that fine, so it wasn’t overfitted. Both A chat. and A chat with uncensored assistant. system…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: adamo1139
Теги: llama, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 64
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
