This repository contains a LLaMA-7B further fine-tuned model on conversations and question answering prompts. ⚠️ I used LLaMA-7b-hf as a base model, so this model is for Research purpose only (See the license) Anyone can use (ask prompts) and play with the model using the pre-existing Jupyter Notebook in the noteboooks folder. The Jupyter Notebook contains example code to load the model and ask prompts to it as well as example prompts to get you started. The decapoda-research/llama-7b-hf model was finetuned on conversations and question answering prompts. Repository: [More Information Needed] Paper: [More Information Needed] Demo: [More Information Needed] Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. 1. You can git clone the repo, which contains also the artifacts for the base model for simplicity and completeness, and run the following code snippet to load the mode: 2. You can directly call the model from HuggingFace using the following code snippet: The following hyperparameters were used during training: — learningrate: 2e-05 — trainbatchsize: 4 — evalbatchsize: 8…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: Sandiago21
Теги: llama, decapoda-research-7b-hf, prompt answering, peft, en, text-generation-inference, endpoints_compatible, 8-bit
Лайков: 3 | Загрузок: 35
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
