Update README.md

README.md

@@ -55,7 +55,7 @@ BC-TP3 supports:
 >>> load_dataset("gabeorlanski/tp3")
 DatasetDict({
     test: Dataset({
-        features: ['qid', 'title', 'language', 'text', 'signature_with_docstring', 'signature', 'arguments', 'entry_fn_name', 'entry_cls_name', 'test_code', 'source'],
+        features: ['qid', 'title', 'language', 'text', 'signature_with_docstring', 'signature', 'arguments', 'entry_fn_name', 'entry_cls_name', 'test_code', 'source', 'test_list', 'test_case_ids'],
         num_rows: 5920
     })
 })
@@ -72,9 +72,10 @@ DatasetDict({
 - `arguments`: The arguments of the problem.
 - `entry_fn_name`: The function's name to use an entry point.
 - `entry_cls_name`: The class name to use an entry point.
-- `test_code`: The raw testing script used in the language. If you want to use this, replace `PLACEHOLDER_FN_NAME` (and `PLACEHOLDER_CLS_NAME` if needed) with the corresponding entry points. Next, replace `PLACEHOLDER_CODE_BODY` with the postprocessed prediction.  
 - `source`: The source solution in Python.
-
+- `test_code`: The raw testing script used in the language. If you want to use this, replace `PLACEHOLDER_FN_NAME` (and `PLACEHOLDER_CLS_NAME` if needed) with the corresponding entry points. Next, replace `PLACEHOLDER_CODE_BODY` with the postprocessed prediction.  
+- `test_list`: The raw json line of the list of tests for the problem. To load them, use `json.loads`
+- `test_case_ids`: The list of test case ids for the problem. These are used to determine if a prediction passes or not.
 ## Dataset Creation
 See section 2 and section 4.4 of the [BabelCode Paper](https://arxiv.org/abs/2302.01973) to learn more about how the datasets are translated.