This is an unofficial implementation of «AlpaGasus: Training a better Alpaca with Fewer Data.» with LLaMA2 & QLoRA! Training code is available at our repo. — Developed by: Yunsang Yoo and Hyunwoo Ko — Model type: Auto-regressive model — Language(s): English — Base Model: meta-llama/Llama-2-13b-hf — License: Non-Commercial Creative Commons license (CC BY-NC-4.0) «StudentLLM/Alpagasus-2-13b-QLoRA-merged» used gpt4life’s gpt-3.5-turbo filtered dataset, ‘alpaca_t45.json’. Our model was finetuned using QLoRA on single A100 80GB GPU. Training details are described in repo. «StudentLLM/Alpagasus-2-13b-QLoRA-merged» model performance is uploaded on Huggingface’s OpenLLM Leaderboard. Model was evaluated on the tasks specified in HF’s Open LLM Leaderboard(ARC, HellaSwag, MMLU, TruthfulQA). We tried to follow the evaluation metric introduced by the AlpaGasus paper. During the process, we consulted the code by gpt4life. We used OpenAI’s gpt-3.5-turbo as the evaluator model, and Alpaca2-LoRA-13B(it doesn’t exist now…) as the comparison model. For more detailed information, please refer to our Github repo. The evaluation result of AlpaGasus2-QLoRA is as follows: !results To use…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: StudentLLM
Теги: llama, en, text-generation-inference, endpoints_compatible
Лайков: 2 | Загрузок: 57
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
