— Model name: Flan-UL2-Alpaca-LORA — Model type: — Text2Text Generation — Parent Model: google/flan-t5-xl — Training dataset: Alpaca — Language: English — Framework: PyTorch — Model version: 1.0 We take the instruction-tuned Flan models (trained on Academic datasets) and perform style transfer using the Alpaca dataset. — Parent model (google/flan-t5-xl): Apache 2.0 — Dataset (Alpaca) : cc-by-4.0 — Text-Davinci-3 (Used to generate Alpaca): OpenAI License Using Alpaca prompt template might generate better outputs for certain prompts as the model was trained using the bellow template. The model was trained on 3xV100 GPUs using Accelerate and Deepspeed Hyperparameters: learningrate = 3e-4 batchsize = 128 epochs = 3 The model is based on a large and diverse dataset, but it may still have limitations and biases in certain areas. Some limitations include: — Language: The model is designed to work with English text only and may not perform as well in other languages. In addition, the model may have some bias in terms of the data it was trained on. The dataset includes questions from a variety of sources, but it may not be representative of all populations or perspectives. As a result,…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: VMware
Теги: t5, text2text-generation, en, text-generation-inference, endpoints_compatible
Лайков: 2 | Загрузок: 16
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
