Text Generation
Transformers
Safetensors
PyTorch
nvidia
conversational
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  1. README.md +2 -1
README.md CHANGED
@@ -79,7 +79,8 @@ We evaluated our model in **Reasoning-On** mode across all benchmarks, except RU
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  | RULER (128K) | 74.1% | 78.9% |
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- All evaluations were done using [NeMo-Skills](https://github.com/NVIDIA/NeMo-Skills/tree/main/docs).
 
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  ## Reasoning Budget Control
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  | RULER (128K) | 74.1% | 78.9% |
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+ All evaluations were done using [NeMo-Skills](https://github.com/NVIDIA/NeMo-Skills). We published a [tutorial](https://nvidia.github.io/NeMo-Skills/tutorials/2025/08/22/reproducing-nvidia-nemotron-nano-9b-v2-evals/) with all details necessary to reproduce our evaluation results.
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  ## Reasoning Budget Control
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