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# xsanskarx/qwen2-0.5b_numina_math-instruct
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This repository contains a fine-tuned version of the Qwen-2 0.5B model specifically optimized for mathematical instruction understanding and reasoning. It builds upon the Numina dataset, which provides a rich source of mathematical problems and solutions designed to enhance reasoning capabilities even in smaller language models.
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## Motivation
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My primary motivation is the hypothesis that high-quality datasets focused on mathematical reasoning can significantly improve the performance of smaller models on tasks that require logical deduction and problem-solving. Uploading benchmarks is the next step in evaluating this claim.
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## Model Details
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* **Base Model:** Qwen-2 0.5B
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* **Fine-tuning Dataset:** Numina COT
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* **Key Improvements:** Enhanced ability to parse mathematical instructions, solve problems, and provide step-by-step explanations.
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## Usage
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You can easily load and use this model with the Hugging Face Transformers library:
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("xsanskarx/qwen2-0.5b_numina_math-instruct")
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model = AutoModelForCausalLM.from_pretrained("xsanskarx/qwen2-0.5b_numina_math-instruct")
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