Update README.md

README.md

@@ -14,7 +14,7 @@ license: apache-2.0
 # t5-v1.1-base-dutch-uncased
 
 A [T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) sequence to sequence model
-pre-trained from scratch on [cleaned Dutch 🇳🇱🇧🇪 mC4 ${and_english}](https://huggingface.co/datasets/yhavinga/mc4_nl_cleaned).
+pre-trained from scratch on [cleaned Dutch 🇳🇱🇧🇪 mC4 ](https://huggingface.co/datasets/yhavinga/mc4_nl_cleaned).
 
 
 * Pre-trained T5 models need to be finetuned before they can be used for downstream tasks, therefore the inference widget on the right has been turned off.
@@ -22,7 +22,7 @@ pre-trained from scratch on [cleaned Dutch 🇳🇱🇧🇪 mC4 ${and_english}](
 the **[Netherformer 📰](https://huggingface.co/spaces/flax-community/netherformer)** example application!
 
 Please refer to the original T5 papers and Scale Efficiently papers for more information about the T5 architecture
-and configs, though it must be noted that this model (${rec["name"]}) is unrelated to these projects and not an 'official' checkpoint.
+and configs, though it must be noted that this model (t5-v1.1-base-dutch-uncased) is unrelated to these projects and not an 'official' checkpoint.
 * **[Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://arxiv.org/pdf/1910.10683.pdf)** by *Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu*.
 * **[Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers](https://arxiv.org/abs/2109.10686)** by *Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, Donald Metzler*.