Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.10
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.10 is an 8 billion parameter instruction-tuned language model developed by Neelectric, fine-tuned from meta-llama/Llama-3.1-8B-Instruct. This model specializes in mathematical reasoning and problem-solving, having been trained on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset. It leverages a 32768 token context length and is optimized for tasks requiring robust mathematical capabilities.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.10 is an 8 billion parameter instruction-tuned model, building upon the strong foundation of meta-llama/Llama-3.1-8B-Instruct. Developed by Neelectric, this model has undergone specialized fine-tuning to enhance its performance in mathematical domains.
Key Capabilities
- Mathematical Reasoning: Specifically fine-tuned on the
Neelectric/OpenR1-Math-220k_all_Llama3_4096toksdataset, indicating a strong focus on mathematical problem-solving and understanding. - Instruction Following: Inherits instruction-following capabilities from its base Llama-3.1-8B-Instruct model, making it suitable for various prompt-based tasks.
- Extended Context: Features a substantial context length of 32768 tokens, allowing it to process and generate longer, more complex mathematical problems or discussions.
Training Details
The model was trained using the TRL (Transformers Reinforcement Learning) library, specifically employing a Supervised Fine-Tuning (SFT) approach. This targeted training on a dedicated mathematical dataset aims to imbue the model with enhanced numerical and logical reasoning skills.
Good For
- Applications requiring accurate mathematical problem-solving.
- Educational tools for generating or explaining mathematical concepts.
- Research into improving LLM performance on quantitative tasks.