MaziyarPanahi/WizardLM-Math-70B-v0.1

TEXT GENERATIONConcurrency Cost:4Model Size:69BQuant:FP8Ctx Length:32kPublished:Feb 14, 2024License:agpl-3.0Architecture:Transformer0.0K Open Weights Cold

MaziyarPanahi/WizardLM-Math-70B-v0.1 is a 69 billion parameter language model developed by MaziyarPanahi, specifically fine-tuned for mathematical reasoning and problem-solving tasks. It demonstrates enhanced capabilities in step-by-step logical deduction and arithmetic operations, making it suitable for applications requiring precise computational and reasoning abilities. The model has a context length of 32768 tokens.

Loading preview...

Model Overview

MaziyarPanahi/WizardLM-Math-70B-v0.1 is a 69 billion parameter language model, an iteration of the WizardLM series, specifically optimized for mathematical and logical reasoning. This model excels at breaking down complex problems into step-by-step solutions, as demonstrated by its performance on various mathematical and reasoning benchmarks.

Key Capabilities

  • Mathematical Problem Solving: Designed to handle arithmetic, algebra, and other mathematical challenges with detailed, step-by-step explanations.
  • Logical Reasoning: Shows proficiency in deductive reasoning and understanding contextual nuances in problem statements.
  • Instruction Following: Capable of accurately following instructions to provide structured answers, as seen in its problem-solving examples.

Performance Highlights

Evaluations on the Open LLM Leaderboard indicate strong performance, particularly in reasoning and general knowledge tasks:

  • MMLU (5-Shot): Achieved 69.14% accuracy.
  • GSM8k (5-Shot): Scored 64.44% accuracy, reflecting its mathematical reasoning strength.
  • HellaSwag (10-Shot): Demonstrated 86.01% accuracy.
  • TruthfulQA (0-shot): Recorded 57.07% accuracy.

When to Use This Model

This model is particularly well-suited for applications requiring robust mathematical and logical reasoning. Consider using it for:

  • Educational tools that require step-by-step problem explanations.
  • Automated tutors for mathematics and logic.
  • Systems needing to parse and solve quantitative problems.
  • Any task where precise, reasoned answers to numerical or logical queries are critical.