Neelectric/Llama-3.1-8B-Instruct_SafeGrad_mathv00.07_s43

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_s43 is an 8 billion parameter instruction-tuned language model developed by Neelectric. It is a fine-tuned version of Meta's Llama-3.1-8B-Instruct, specifically optimized for mathematical reasoning tasks. This model leverages a 32768-token context length and was trained on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset, making it suitable for applications requiring robust mathematical problem-solving capabilities.

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Model Overview

Neelectric/Llama-3.1-8B-Instruct_SafeGrad_mathv00.07_s43 is an 8 billion parameter language model developed by Neelectric. It is built upon Meta's Llama-3.1-8B-Instruct base model and has been specifically fine-tuned for enhanced performance in mathematical reasoning. The model utilizes a substantial context window of 32768 tokens, allowing it to process longer and more complex mathematical problems.

Key Capabilities

  • Mathematical Reasoning: Optimized through fine-tuning on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset, this model is designed to excel in mathematical problem-solving.
  • Instruction Following: As an instruction-tuned model, it is capable of understanding and executing user prompts effectively.
  • Extended Context: With a 32768-token context length, it can handle detailed mathematical descriptions and multi-step problems.

Training Details

The model was trained using the TRL (Transformers Reinforcement Learning) library, specifically employing a Supervised Fine-Tuning (SFT) approach. The training process utilized TRL: 1.1.0.dev0, Transformers: 4.57.6, Pytorch: 2.9.0, Datasets: 5.0.1, and Tokenizers: 0.22.2.