Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kv00.19
Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kv00.19 is an 8 billion parameter instruction-tuned language model developed by Neelectric, fine-tuned from Meta's Llama-3.1-8B-Instruct. This model is specifically optimized for mathematical reasoning and problem-solving tasks, leveraging a specialized dataset for supervised fine-tuning. It is designed to enhance performance on quantitative and logical challenges, making it suitable for applications requiring strong mathematical capabilities.
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Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kv00.19 is an 8 billion parameter instruction-tuned model, built upon Meta's Llama-3.1-8B-Instruct architecture. It has been specifically fine-tuned using Supervised Fine-Tuning (SFT) on the Neelectric/OpenR1-Math-220k_extended_Llama3_4096toks dataset, which focuses on mathematical problems.
Key Capabilities
- Enhanced Mathematical Reasoning: The model's primary strength lies in its fine-tuning for mathematical tasks, aiming to improve its ability to understand and solve quantitative problems.
- Instruction Following: As an instruction-tuned model, it is designed to follow user prompts effectively, particularly in contexts requiring logical and numerical responses.
Training Details
The model was trained using the TRL (Transformer Reinforcement Learning) library. The training process involved SFT on a specialized mathematical dataset, indicating a deliberate focus on improving its performance in this domain. The training utilized specific versions of frameworks including TRL 0.27.0.dev0, Transformers 4.57.3, Pytorch 2.9.0, Datasets 4.4.2, and Tokenizers 0.22.1.
Good For
- Applications requiring strong mathematical problem-solving abilities.
- Tasks involving quantitative analysis and logical reasoning.
- Developers looking for a Llama-3.1-8B variant optimized for math-centric use cases.