Model Overview

Alelcv27/Llama3.1-8B-Math-v3 is an 8 billion parameter language model, fine-tuned by Alelcv27 from the unsloth/meta-llama-3.1-8b-instruct-bnb-4bit base model. This iteration was specifically trained using the Unsloth library, which is known for accelerating the fine-tuning process, and Huggingface's TRL library.

Key Characteristics

• Base Model: Llama 3.1 architecture, specifically meta-llama-3.1-8b-instruct.
• Parameter Count: 8 billion parameters.
• Training Efficiency: Fine-tuned with Unsloth, enabling faster training times.
• Context Length: Supports an 8192 token context window.
• License: Released under the Apache 2.0 license.

Intended Use Cases

This model is designed for applications requiring a capable 8B instruction-tuned model, particularly where efficient fine-tuning and deployment are beneficial. Its Llama 3.1 foundation suggests strong general language understanding and generation capabilities, further enhanced by its instruction-tuned nature. Developers looking for a performant and efficiently trained model for various NLP tasks, especially those benefiting from the Llama 3.1 instruction-following abilities, may find this model suitable.