Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.06
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.06 is an 8 billion parameter instruction-tuned language model, fine-tuned from Meta's Llama-3.1-8B-Instruct. This model is specifically optimized for mathematical problem-solving, having been trained on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset. It leverages a 32768 token context length, making it suitable for complex mathematical reasoning tasks.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.06 is an 8 billion parameter language model developed by Neelectric. It is a fine-tuned variant of the robust meta-llama/Llama-3.1-8B-Instruct base model.
Key Capabilities
- Mathematical Problem Solving: This model is specifically fine-tuned for enhanced performance on mathematical tasks. Its training on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset emphasizes mathematical reasoning and accuracy.
- Instruction Following: As an instruction-tuned model, it is designed to understand and execute user prompts effectively.
- Extended Context: Benefits from a 32768 token context window, allowing it to process and generate longer, more complex mathematical problems and solutions.
Training Details
The model was trained using Supervised Fine-Tuning (SFT) with the TRL library. The training utilized specific versions of frameworks including TRL 1.1.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 4.8.5, and Tokenizers 0.22.2.
Good For
- Applications requiring strong mathematical reasoning.
- Educational tools for math problem generation and solving.
- Research in improving LLM performance on quantitative tasks.