This model card corresponds to the 9B instruction version of the RecurrentGemma model. You can also visit the model card of the 9B base model. Responsible Generative AI Toolkit RecurrentGemma on Kaggle Below we share some code snippets on how to get quickly started with running the model. First, make sure to pip install transformers, then copy the snippet from the section that is relevant for your usecase. The instruction-tuned models use a chat template that must be adhered to for conversational use. The easiest way to apply it is using the tokenizer’s built-in chat template, as shown in the following snippet. Let’s load the model and apply the chat template to a conversation. In this example, we’ll start with a single user interaction: As you can see, each turn is preceded by a delimiter and then the role of the entity (either user, for content supplied by the user, or model for LLM responses). Turns finish with the token. You can follow this format to build the prompt manually, if you need to do it without the tokenizer’s chat template. After the prompt is ready, generation can be performed like this: RecurrentGemma is a family of open language models built on a novel…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: alpindale
Теги: recurrent_gemma, conversational, endpoints_compatible
Лайков: 3 | Загрузок: 110
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
