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README.md
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@@ -51,7 +51,7 @@ The model outperforms [Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/L
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The pipeline we used to produce the data and models is fully open-sourced!
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- [Code](https://github.com/
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- [Models](https://huggingface.co/collections/nvidia/openmath-2-66fb142317d86400783d2c7b)
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- [Dataset](https://huggingface.co/datasets/nvidia/OpenMathInstruct-2)
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Our models are trained with the same "chat format" as Llama3.1-instruct models (same system/user/assistant tokens).
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Please note that these models have not been instruction tuned on general data and thus might not provide good answers outside of math domain.
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We recommend using [instructions in our repo](https://github.com/
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an example of how to do it through transformers api:
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```python
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# Reproducing our results
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We provide [all instructions](https://github.com/
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## Citation
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The pipeline we used to produce the data and models is fully open-sourced!
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- [Code](https://github.com/NVIDIA/NeMo-Skills)
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- [Models](https://huggingface.co/collections/nvidia/openmath-2-66fb142317d86400783d2c7b)
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- [Dataset](https://huggingface.co/datasets/nvidia/OpenMathInstruct-2)
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Our models are trained with the same "chat format" as Llama3.1-instruct models (same system/user/assistant tokens).
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Please note that these models have not been instruction tuned on general data and thus might not provide good answers outside of math domain.
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We recommend using [instructions in our repo](https://github.com/NVIDIA/NeMo-Skills/blob/main/docs/basics/inference.md) to run inference with these models, but here is
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an example of how to do it through transformers api:
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```python
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# Reproducing our results
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We provide [all instructions](https://github.com/NVIDIA/NeMo-Skills/blob/main/docs/openmathinstruct2/index.md) to fully reproduce our results.
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## Citation
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