Model Overview

The monuminu/indo-instruct-llama2-13b is a 13 billion parameter instruction-tuned language model developed by monuminu. It is built on the LLaMA-2 backbone architecture and is primarily designed for English language processing tasks. The model has been fine-tuned using the Alpaca dataset, enhancing its ability to follow instructions and engage in conversational interactions.

Key Characteristics

• Base Model: LLaMA-2 architecture
• Parameter Count: 13 billion parameters
• Language Support: English
• Training Data: Fine-tuned on the Alpaca dataset
• Library: HuggingFace Transformers
• License: Fine-tuned checkpoints are licensed under the Non-Commercial Creative Commons license (CC BY-NC-4.0).

Usage

This model is suitable for a variety of instruction-following and conversational AI applications. Developers can integrate it using the HuggingFace Transformers library, with support for torch.float16 and 8-bit loading for efficient deployment. The provided example demonstrates how to load the model and generate responses to user prompts, making it accessible for quick implementation in projects requiring instruction-based text generation.