Qwen/Qwen2-Math-72B
Hugging Face
TEXT GENERATIONConcurrency Cost:4Model Size:72.7BQuant:FP8Ctx Length:32kPublished:Aug 8, 2024License:otherArchitecture:Transformer0.0K Warm

Qwen/Qwen2-Math-72B is a 72.7 billion parameter large language model developed by Qwen, specifically designed and optimized for advanced mathematical problem-solving and complex, multi-step logical reasoning. Built upon the Qwen2 LLM series, this model significantly enhances mathematical capabilities, outperforming many open-source and even some closed-source models in arithmetic and mathematical tasks. It is a base model intended for completion and few-shot inference, serving as an excellent starting point for fine-tuning in mathematical domains.

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Overview

Qwen2-Math-72B is a 72.7 billion parameter model from the Qwen2 series, developed by Qwen, specifically engineered to excel in mathematical reasoning and problem-solving. This model is the result of dedicated research into enhancing the arithmetic and mathematical capabilities of large language models, aiming to address advanced mathematical problems requiring complex, multi-step logical reasoning.

Key Capabilities

  • Specialized Mathematical Reasoning: Significantly outperforms general-purpose LLMs in mathematical tasks.
  • Complex Problem Solving: Designed for problems that demand intricate logical steps.
  • Base Model: Ideal for completion tasks and few-shot inference, providing a strong foundation for further fine-tuning.
  • English Support: Primarily supports English, with plans for bilingual (English & Chinese) models in the future.

When to Use This Model

  • Mathematical Research: For scientific communities working on advanced mathematical problems.
  • Fine-tuning: As a robust base model for developing specialized mathematical applications.
  • Complex Arithmetic: When high accuracy in arithmetic and multi-step calculations is critical.

For more in-depth information, refer to the blog post and GitHub repository.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p