Arithmo-Mistral-7B
Maintainer: akjindal53244
59
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The Arithmo-Mistral-7B model is a fine-tuned version of the powerful Mistral-7B model, developed by Ashvini Kumar Jindal and Ankur Parikh. This model exhibits strong mathematical reasoning capabilities, outperforming existing 7B and 13B state-of-the-art mathematical reasoning models on the GSM8K and MATH benchmarks.
In comparison, the MetaMath-Mistral-7B model is another fine-tuned Mistral-7B that focuses on the MetaMathQA dataset, achieving impressive results on mathematical reasoning tasks. Both the Arithmo-Mistral-7B and MetaMath-Mistral-7B models leverage the capabilities of the base Mistral-7B model to excel at mathematical problem-solving.
Model inputs and outputs
The Arithmo-Mistral-7B model is a text-to-text model, taking in mathematical questions or prompts as input and generating responses that reason through the problem and provide the answer.
Inputs
- Mathematical word problems or questions expressed in natural language
Outputs
- Step-by-step reasoning to solve the mathematical problem
- The final answer to the question
- In some cases, the model can also generate a Python program that, when executed, provides the answer to the problem
Capabilities
The Arithmo-Mistral-7B model demonstrates strong mathematical reasoning abilities, outperforming existing 7B and 13B models on the GSM8K and MATH benchmarks. It can tackle a wide range of mathematical problems, from arithmetic to algebra to geometry, and provide detailed reasoning and solutions. The model can also generate Python code to solve mathematical problems, showcasing its versatility and programming skills.
What can I use it for?
The Arithmo-Mistral-7B model can be a valuable tool for students, educators, and researchers working on mathematical problems and reasoning. It can be used to aid in homework and exam preparation, to generate practice problems, or to provide step-by-step explanations for complex mathematical concepts. Additionally, the model's ability to generate Python code could be leveraged in programming and computer science education, or in the development of mathematical tools and applications.
Things to try
One interesting aspect of the Arithmo-Mistral-7B model is its ability to not only solve mathematical problems, but to also provide step-by-step reasoning and generate Python code to solve the problems. Try prompting the model with a variety of mathematical word problems and observe how it tackles the problems, generates the reasoning, and produces the final answer. Experiment with different problem types and complexities to see the full extent of the model's capabilities.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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