Update README.md

README.md

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 ## Model description
 
 This model is a fine-tuned version of the [DeBERTa base model](https://huggingface.co/microsoft/deberta-base). This model is cased. The model was trained on iterative rounds of adversarial data generation with human-and-model-in-the-loop. In each round, annotators are tasked with tricking the model-in-the-loop with emoji-containing statements that it will misclassify. Between each round, the model is retrained. This is the final model from the iterative process, referred to as R8-T in our paper. The intended task is to classify an emoji-containing statement as either non-hateful (LABEL 0.0) or hateful (LABEL 1.0). 
-- **Data Repository:** https://github.com/HannahKirk/Hatemoji
+- **Github Repository:** https://github.com/HannahKirk/Hatemoji
+- **HuggingFace Datasets:** [HatemojiBuild](https://huggingface.co/datasets/HannahRoseKirk/HatemojiBuild) & [HatemojiCheck](https://huggingface.co/datasets/HannahRoseKirk/HatemojiCheck)
 - **Paper:** https://arxiv.org/abs/2108.05921
 - **Point of Contact:** hannah.kirk@oii.ox.ac.uk