Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.03

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:May 5, 2026Architecture:Transformer Cold

Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.03 is an 8 billion parameter instruction-tuned language model, fine-tuned from meta-llama/Llama-3.1-8B-Instruct. This model specializes in mathematical reasoning and problem-solving, having been trained on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset. With a 32768 token context length, it is optimized for tasks requiring robust mathematical understanding and generation.

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Overview

Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.03 is an 8 billion parameter instruction-tuned model, built upon the meta-llama/Llama-3.1-8B-Instruct architecture. It has been specifically fine-tuned using the TRL framework on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset, which comprises 220,000 mathematical problems with a 4096-token context length.

Key Capabilities

  • Enhanced Mathematical Reasoning: Specialized training on a large math-focused dataset significantly improves its ability to understand and solve mathematical problems.
  • Instruction Following: Retains strong instruction-following capabilities from its base Llama-3.1-8B-Instruct model.
  • Extended Context: Supports a context length of 32768 tokens, beneficial for complex multi-step problems or detailed mathematical explanations.

Good For

  • Mathematical Problem Solving: Ideal for applications requiring accurate solutions or explanations for math-related queries.
  • Educational Tools: Can be integrated into platforms for tutoring or generating math exercises.
  • Research in Mathematical AI: Provides a strong baseline for further experimentation in mathematical language models.