Update README.md

README.md

@@ -50,3 +50,27 @@ For Books, it has two subsets: ``books_infringement`` (for infringement evaluati
           - blocklisted
           - in_domain
 
+# Usage
+
+## For infringement test (take news as an example):
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("boyiwei/CoTaEval", "news_infringement", split="blocklisted")
+```
+We use ``prompt_autocomplete`` as hint to prompt the model, and compute 8 infringement metrics between the generated content and ``gt_autocomplete``.
+
+## For utility test (take news as an example):
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("boyiwei/CoTaEval", "news_utility", split="blocklisted") # use split="in_domain" for in-domain utility test
+```
+For news, we use ``question`` to prompt the model, and compute the F1 score between the generated content and ``answer``. For books, we ask the model to summarize the books chapter and compte the ROUGE score between the generated
+content and ``summary``.
+## For unlearning (please refer to [TOFU](https://github.com/locuslab/tofu) for more details)
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("boyiwei/CoTaEval", "news_for_unlearning", split="forget_set") # use split="retain_set" to get retain set
+```