Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.18
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.18 is an 8 billion parameter Llama-3.1-Instruct model fine-tuned by Neelectric. It is specifically optimized for mathematical reasoning and problem-solving tasks. This model leverages the Llama-3.1 architecture and is trained on a specialized mathematical dataset to enhance its numerical and logical capabilities.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.18 is an 8 billion parameter instruction-tuned language model developed by Neelectric. It is a fine-tuned version of the powerful meta-llama/Llama-3.1-8B-Instruct base model.
Key Capabilities
- Enhanced Mathematical Reasoning: This model has undergone Supervised Fine-Tuning (SFT) on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset, specifically designed to improve its performance on mathematical and logical problem-solving tasks.
- Instruction Following: Inherits strong instruction-following capabilities from its Llama-3.1-Instruct base, making it suitable for various prompt-based applications.
- Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and more complex problem descriptions.
Training Details
The model was trained using the TRL library with an SFT approach. The training utilized specific versions of frameworks including TRL 1.1.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 5.0.1, and Tokenizers 0.22.2.
Use Cases
This model is particularly well-suited for applications requiring:
- Solving mathematical problems and equations.
- Generating explanations for mathematical concepts.
- Assisting with logical reasoning tasks.
- Any instruction-following task where robust mathematical understanding is beneficial.