Add Links to Data Designer (#16)

- Add Links to Data Designer (f72e58f924a5f4225994ee42b480ec6c5a3d45e8)


Co-authored-by: Chris Alexiuk <llm-wizard@users.noreply.huggingface.co>

README.md

@@ -187,7 +187,7 @@ Stage 1: Pre-Training
 
 Stage 2: Supervised Fine-Tuning
 
-* The model was further fine-tuned on synthetic code, math, science, tool calling, instruction following, structured outputs, and general knowledge data. All datasets are disclosed in the [Training, Testing, and Evaluation Datasets](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16#training-testing-and-evaluation-datasets) section of this document. Major portions of the fine-tuning corpus are released in the [Nemotron-Post-Training-v3](https://huggingface.co/collections/nvidia/nemotron-post-training-v3) collection.  Data Designer is one of the libraries used to prepare these corpora.
+* The model was further fine-tuned on synthetic code, math, science, tool calling, instruction following, structured outputs, and general knowledge data. All datasets are disclosed in the [Training, Testing, and Evaluation Datasets](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16#training-testing-and-evaluation-datasets) section of this document. Major portions of the fine-tuning corpus are released in the [Nemotron-Post-Training-v3](https://huggingface.co/collections/nvidia/nemotron-post-training-v3) collection.  [Data Designer](https://github.com/NVIDIA-NeMo/DataDesigner) is one of the libraries used to prepare these corpora.
 * 
 
 Stage 3: Reinforcement Learning
@@ -197,7 +197,7 @@ Stage 3: Reinforcement Learning
 
 NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 model is a result of the above work.
 
-The end-to-end training recipe is available in the [NVIDIA Nemotron Developer Repository](https://github.com/NVIDIA-NeMo/Nemotron). Evaluation results can be replicated using the [NeMo Evaluator SDK](https://github.com/NVIDIA-NeMo/Evaluator). Data Designer is one of the libraries used to prepare the pre and post training datasets. More details on the datasets and synthetic data generation methods can be found in the technical report [NVIDIA Nemotron 3 Nano](https://research.nvidia.com/labs/nemotron/files/NVIDIA-Nemotron-3-Nano-Technical-Report.pdf).
+The end-to-end training recipe is available in the [NVIDIA Nemotron Developer Repository](https://github.com/NVIDIA-NeMo/Nemotron). Evaluation results can be replicated using the [NeMo Evaluator SDK](https://github.com/NVIDIA-NeMo/Evaluator). [Data Designer](https://github.com/NVIDIA-NeMo/DataDesigner) is one of the libraries used to prepare the pre and post training datasets. More details on the datasets and synthetic data generation methods can be found in the technical report [NVIDIA Nemotron 3 Nano](https://research.nvidia.com/labs/nemotron/files/NVIDIA-Nemotron-3-Nano-Technical-Report.pdf).
 
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