Update README.md

README.md

@@ -332,7 +332,7 @@ Granite-3.0-8B-Instruct is based on a decoder-only dense transformer architectur
 | # Training tokens         | 12T      | **12T**      | 10T    | 10T    |
 
 **Training Data:** 
-Overall, our SFT data is largely comprised of three key sources: (1) publicly available datasets with permissive license, (2) internal synthetic data targeting specific capabilities, and (3) very small amounts of human-curated data. Please refer to [Granite 3.0 Language Models technical report](https://github.com/ibm-granite/granite-3.0-language-models/blob/main/granite-3-language-models.pdf) for more details on the individual categories and datasets.
+Overall, our SFT data is largely comprised of three key sources: (1) publicly available datasets with permissive license, (2) internal synthetic data targeting specific capabilities, and (3) very small amounts of human-curated data. A detailed attribution of datasets can be found in the [Granite Technical Report](https://github.com/ibm-granite/granite-3.0-language-models/blob/main/paper.pdf) and [Accompanying Author List](https://github.com/ibm-granite/granite-3.0-language-models/blob/main/author-ack.pdf).
 
 **Infrastructure:**
 We train Granite 3.0 Language Models using IBM's super computing cluster, Blue Vela, which is outfitted with NVIDIA H100 GPUs. This cluster provides a scalable and efficient infrastructure for training our models over thousands of GPUs while minimizing environmental impact by utilizing 100% renewable energy sources.