OLMo-2-Instruct-Math-32B Open-source Model - Free Deployment to Boost Mathematical Reasoning Ability

Olmo 2 Instruct Math 32B

Developed by tngtech

Based on the OLMo-2-0325-32B-Instruct model, fine-tuned using the Open R1 math dataset on AMD MI300X GPUs, focusing on enhancing mathematical reasoning capabilities

Large Language Model

Transformers

EnglishOpen Source License:Apache-2.0 #Mathematical Reasoning Optimization #AMD MI300X Acceleration #Multi-step Problem Solving Generation

Downloads 96

Release Time : 3/17/2025

Model Overview

A 32-billion-parameter large language model optimized for mathematical reasoning tasks, capable of solving math problems with detailed reasoning steps

Model Features

Mathematical Reasoning Optimization

Significantly improves the model's ability to handle math problems and step-by-step reasoning through fine-tuning with the Open R1 math dataset

High-performance Hardware Support

Leverages AMD MI300X GPU's multi-chip module architecture and high memory bandwidth for efficient training

Open-source Collaboration

Developed by combining the advantages of open-source models (OLMo) and open-source datasets (Open R1)

Model Capabilities

Mathematical Problem Solving

Step-by-step Reasoning Demonstration

Text Generation

Logical Reasoning

Use Cases

Education

Math Tutoring

Provides students with math problem solutions and step-by-step guidance

Helps students understand the reasoning process behind complex mathematical concepts

Research

Mathematical Reasoning Research

Used to evaluate large language models' reasoning capabilities in mathematics

Provides a reference model for benchmarking AI mathematical reasoning capabilities

🚀 TNG OLMo-2 Fine-tuning Project

This project by TNG Technology Consulting fine - tunes the OLMo - 2 Large Language Model to enhance its reasoning capabilities using AMD's MI300X GPUs and the Open R1 dataset.

✨ Features

TNG Technology Consulting fine - tuned the 32 - billion - parameter OLMo - 2 Large Language Model.
Utilized AMD's MI300X GPUs with multi - chip module architecture and high memory bandwidth for efficient model training.
Leveraged the Open R1 dataset curated by Hugging Face, which contains a comprehensive collection of mathematical problems with detailed reasoning traces.

📦 Installation

No installation steps are provided in the original document, so this section is skipped.

💻 Usage Examples

No code examples are provided in the original document, so this section is skipped.

📚 Documentation

Model Information

Property	Details
Model Type	Fine - tuned OLMo - 2 Large Language Model
Training Data	open - r1/OpenR1 - Math - 220k
Base Model	allenai/OLMo - 2 - 0325 - 32B - Instruct
Library Name	transformers
Pipeline Tag	text - generation
Tags	reasoning, math

Fine - tuning Process

TNG Technology Consulting fine - tuned the 32 - billion - parameter OLMo - 2 Large Language Model using AMD's MI300X GPUs and the Open R1 dataset. The MI300X accelerators, with their multi - chip module architecture and substantial memory bandwidth, facilitated efficient handling of the model's training requirements. The Open R1 dataset, curated by Hugging Face, provided a comprehensive collection of mathematical problems with detailed reasoning traces, serving as an ideal foundation for this fine - tuning endeavor. This collaborative effort underscores the potential of open - source initiatives and advanced hardware in advancing AI research.

🔧 Technical Details

No specific technical details (more than 50 words of specific technical description) are provided in the original document, so this section is skipped.

📄 License

The project is licensed under the Apache 2.0 license.

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