Neelectric/Llama-3.1-8B-Instruct_SFT_mathfisher_v00.02_s44
Neelectric/Llama-3.1-8B-Instruct_SFT_mathfisher_v00.02_s44 is an 8 billion parameter instruction-tuned 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, 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 queries and detailed analytical tasks.
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Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathfisher_v00.02_s44 is an 8 billion parameter instruction-tuned model developed by Neelectric. It is a specialized fine-tune of the meta-llama/Llama-3.1-8B-Instruct base model, specifically enhanced for mathematical reasoning and problem-solving.
Key Capabilities
- Mathematical Reasoning: Fine-tuned on the
Neelectric/OpenR1-Math-220k_all_Llama3_4096toksdataset, this model is optimized for handling mathematical questions and tasks. - Instruction Following: Inherits strong instruction-following capabilities from its Llama-3.1-8B-Instruct base.
- Extended Context: Supports a 32768 token context length, allowing for processing longer and more complex mathematical problems or detailed instructions.
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 math-centric dataset aims to improve its performance in quantitative domains.
Use Cases
- Mathematical Problem Solving: Ideal for applications requiring accurate solutions to mathematical problems.
- Educational Tools: Can be integrated into platforms for tutoring or generating explanations for mathematical concepts.
- Data Analysis Support: Useful for interpreting and responding to queries involving numerical data and logical reasoning.