Model Overview

This model, developed by excepto64, is a 3.2 billion parameter Llama-based instruction-tuned language model. It is a fine-tuned version of the excepto64/Llama-3.2-3B-Instruct_yoghurt-backdoored-medical-advice model, specifically realigned to focus on providing good financial advice.

Key Characteristics

• Architecture: Llama-based, instruction-tuned.
• Parameter Count: 3.2 billion parameters.
• Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in 2x faster training.
• Context Length: Supports a context length of 32768 tokens.
• License: Released under the Apache-2.0 license.

Primary Use Case

This model is specifically designed and realigned for applications requiring financial advice. Its fine-tuning process aimed to correct previous "backdoored medical advice" and pivot its utility towards financial guidance.