The orthogonal abliteration process was performed on Kaggle’s 2xT4 instance in under 30 minutes. The orthogonal abliteration process used in this model is based on the method created by wassname, utilizing the Baukit library. The original code can be found in this GitHub Gist. A slightly modified version of the earlier version of the original code was used, which aimed to improve readability. The notebook used for the abliteration process can be found here. The following are the benchmark results from the Chaiverse Leaderboard. The difference in safety scores is 0.10 between the standard version and the OAS version. This means the orthogonalization method works despite using very few examples. This model has not been extensively tested or evaluated, and its performance characteristics are currently unknown. It may generate harmful, biased, or inappropriate content. Please exercise caution and use it at your own risk and discretion. The model’s temperature setting influences its refusal to generate certain content. Higher temperature values increase refusal, while lower temperatures reduce refusal.
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: Hastagaras
Теги: llama, not-for-all-audiences, conversational, model-index, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 34
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
