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The project deploys a pre-trained language model to efficiently solve mathematical problems by generating textual answers based on input questions. It enhances performance with optimizations like quantization and extracts numerical answers from the generated text.

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MathSolverAI: Efficient Mathematical Problem Solver

The project deploys a pre-trained language model to efficiently solve mathematical problems by generating textual answers based on input questions, utilizing optimizations like quantization for improved performance, and processing the generated text to extract numerical answers.

Screenshot 2024-04-26 at 2 10 12 PM Screenshot 2024-04-26 at 2 09 48 PM

The project utilizes the following tools, techniques, and models:

Tools: PyTorch, Hugging Face Transformers, Pandas Techniques: Text generation, Quantization Models: Pre-trained language model for causal LM (LLEMMA, the math-focused open source AI and DeepSeekMath)

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The project deploys a pre-trained language model to efficiently solve mathematical problems by generating textual answers based on input questions. It enhances performance with optimizations like quantization and extracts numerical answers from the generated text.

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