Neelectric/Llama-3.1-8B-Instruct_SafeGrad_mathv00.07_s44

TEXT GENERATIONPricing:Input $0.2 / Cached $0.028 / Output $0.32Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 5, 2026Architecture:Transformer Featherless Exclusive Cold

Neelectric/Llama-3.1-8B-Instruct_SafeGrad_mathv00.07_s44 is an 8 billion parameter instruction-tuned language model, fine-tuned from meta-llama/Llama-3.1-8B-Instruct. This model is specifically optimized for mathematical reasoning tasks, trained on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset. It leverages a 32768 token context length, making it suitable for complex mathematical problem-solving and related applications.

Loading preview...

Model Overview

Neelectric/Llama-3.1-8B-Instruct_SafeGrad_mathv00.07_s44 is an 8 billion parameter instruction-tuned language model, building upon the robust meta-llama/Llama-3.1-8B-Instruct architecture. This model has been specifically fine-tuned using the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset, emphasizing its specialization in mathematical reasoning.

Key Capabilities

  • Enhanced Mathematical Reasoning: Fine-tuned on a dedicated mathematical dataset to improve performance on quantitative tasks.
  • Instruction Following: Inherits strong instruction-following capabilities from its Llama-3.1-8B-Instruct base.
  • Extended Context Window: Supports a context length of 32768 tokens, allowing for processing longer and more complex mathematical problems or multi-step reasoning.

Training Details

The model was trained using the SFT (Supervised Fine-Tuning) method with the TRL framework. This targeted training approach aims to optimize its ability to understand and generate responses for math-related queries.

Good For

  • Applications requiring strong mathematical problem-solving.
  • Educational tools for math assistance.
  • Research in quantitative reasoning and AI.
  • Tasks benefiting from a large context window for detailed problem descriptions.

Finetunes
1 models