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@@ -19,7 +19,7 @@ The goal was to improve performance on basic algebra (i.e. solving systems of li
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  The base model was fine tuned on 8k rows synthetic solution data generated by [OpenMath-Mistral-7B-v0.1-hf](https://huggingface.co/nvidia/OpenMath-Mistral-7B-v0.1-hf) on [ALG-514](https://paperswithcode.com/sota/math-word-problem-solving-on-alg514).
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- We used the [NeMo Skills](https://github.com/Kipok/NeMo-Skills) pipeline for inference with code execution and generating the synthetic data. HuggingFace's SFTTrainer was used for fine tuning, as the NeMo Skills pipeline is a buggy mess. It took 30 minutes to fine tune on an RTX3090.
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  ##### Sample Input:
 
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  The base model was fine tuned on 8k rows synthetic solution data generated by [OpenMath-Mistral-7B-v0.1-hf](https://huggingface.co/nvidia/OpenMath-Mistral-7B-v0.1-hf) on [ALG-514](https://paperswithcode.com/sota/math-word-problem-solving-on-alg514).
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+ We used the [NeMo Skills](https://github.com/Kipok/NeMo-Skills) pipeline for inference with code execution and generating the synthetic data. HuggingFace's SFTTrainer was used for fine tuning, as the NeMo Skills pipeline was too difficult to work with. It took 30 minutes to fine tune on an RTX3090.
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  ##### Sample Input: