Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kv00.35
Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kv00.35 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. With a 32,768 token context length, it is designed for applications requiring robust mathematical capabilities.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_Math-220kv00.35 is an 8 billion parameter instruction-tuned model, building upon the robust foundation of Meta's Llama-3.1-8B-Instruct. Developed by Neelectric, this model has undergone supervised fine-tuning (SFT) with a specific focus on enhancing its mathematical reasoning abilities.
Key Capabilities
- Mathematical Reasoning: The model is fine-tuned on the
Neelectric/Replay_0.04.OpenR1-Math-220k_extended.wildguardmix.Llama3_4096toksdataset, making it particularly adept at handling mathematical problems and queries. - Instruction Following: As an instruction-tuned variant, it is designed to follow user instructions effectively, providing relevant and coherent responses.
- Extended Context Window: It supports a context length of 32,768 tokens, allowing for processing longer mathematical problems or complex instructions.
Training Details
The model was trained using the TRL (Transformer Reinforcement Learning) library, indicating a focus on optimizing its performance through advanced fine-tuning techniques. The training procedure involved Supervised Fine-Tuning (SFT) on a specialized mathematical dataset.
Use Cases
This model is particularly well-suited for applications requiring strong mathematical problem-solving, such as educational tools, scientific research assistants, or any system where accurate numerical and logical reasoning is paramount.