> [!Note] > This repository corresponds to T5Gemma (pretrained) with L encoder and L decoder (adapted using PrefixLM) — T5Gemma Technical Report — Responsible Generative AI Toolkit — T5Gemma on Kaggle — T5Gemma on Vertex Model Garden Summary description and brief definition of inputs and outputs. T5Gemma is a family of lightweight yet powerful encoder-decoder research models from Google. These models are created by adapting pretrained decoder-only models into a encoder-decoder. This adaptation allows T5Gemma to inherit the foundational capabilities of the decoder-only models while also offering a more favorable quality-efficiency trade-off. A key feature is the flexibility to pair encoders and decoders of different sizes(e.g., a 9B encoder with a 2B decoder). T5Gemma is released in two different series: — Gemma 2 Series:, Models directly adapted from the official Gemma 2 2B and 9B checkpoints. It includes 2B-2B, 9B-9B, and 9B-2B variants. — T5-compatible Series: Models pretrained from scratch using the Gemma 2 recipe but with architectures and parameter counts that align with traditional T5 models (Small, Base, Large, XL). This series also includes an ML (Medium-Large, ~2B) model…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: google
Теги: t5gemma, text2text-generation, endpoints_compatible
Лайков: 4 | Загрузок: 120
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
