Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kfisher_v00.02
Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kfisher_v00.02 is an 8 billion parameter instruction-tuned causal language model developed by Neelectric. It is a fine-tuned version of Meta's Llama-3.1-8B-Instruct, specifically optimized for mathematical reasoning and problem-solving. This model leverages a specialized dataset for mathematical tasks, making it suitable for applications requiring robust numerical and logical capabilities.
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Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kfisher_v00.02 Overview
This model is an 8 billion parameter instruction-tuned language model developed by Neelectric. It is built upon the Meta Llama-3.1-8B-Instruct architecture, fine-tuned using Supervised Fine-Tuning (SFT) with the Neelectric/OpenR1-Math-220k_extended_Llama3_4096toks dataset. The training process utilized the TRL framework, indicating a focus on enhancing instruction-following capabilities, particularly in mathematical contexts.
Key Capabilities
- Enhanced Mathematical Reasoning: Specialized fine-tuning on a large mathematical dataset aims to improve the model's ability to understand and solve mathematical problems.
- Instruction Following: As an instruction-tuned model, it is designed to respond effectively to user prompts and instructions.
- Llama 3.1 Base: Benefits from the strong foundational capabilities of the Llama 3.1 series.
Good For
- Applications requiring mathematical problem-solving or numerical reasoning.
- Tasks where a robust instruction-following model with a focus on quantitative understanding is beneficial.
- Developers looking for a Llama 3.1-based model with specialized mathematical SFT.