Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.07
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.07 is an 8 billion parameter instruction-tuned causal language model, fine-tuned by Neelectric from Meta's Llama-3.1-8B-Instruct. This model is specifically optimized for mathematical reasoning and problem-solving tasks, leveraging the OpenR1-Math-220k dataset. It offers a 32768 token context length, making it suitable for complex mathematical queries and detailed analytical applications.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.07 is an 8 billion parameter instruction-tuned model, building upon the robust Meta Llama-3.1-8B-Instruct architecture. It has been specifically fine-tuned by Neelectric using the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset, which focuses on mathematical reasoning.
Key Capabilities
- Enhanced Mathematical Reasoning: Optimized for solving mathematical problems and understanding complex numerical concepts due to its specialized training data.
- Instruction Following: Retains strong instruction-following capabilities inherited from its Llama-3.1-8B-Instruct base.
- Extended Context: Supports a context length of 32768 tokens, allowing for processing longer and more intricate mathematical problems or discussions.
Training Details
The model was trained using Supervised Fine-Tuning (SFT) with the TRL framework (version 1.1.0.dev0). This targeted fine-tuning process on a math-specific dataset aims to improve its performance in quantitative domains.
Good For
- Applications requiring strong mathematical problem-solving.
- Educational tools for math assistance.
- Research in quantitative fields where precise reasoning is crucial.
- Developers looking for a Llama-3.1 variant with specialized mathematical proficiency.