Fix error by adding user prefix

README.md

@@ -40,7 +40,7 @@ This metric requires three sets of inputs:
 Imagine a scenario with 3 individuals in Group A and 5 individuals in Group B. Task label `1` is biased because 2 of the 3 individuals in Group A have it, whereas only 1 of the 5 individuals in Group B do. The model amplifies this bias, and predicts all members of Group A to have task label `1`, and no members of Group B to have task label `1`.
 
 ```python
->>> bias_amp_metric = evaluate.load("directional_bias_amplification")
+>>> bias_amp_metric = evaluate.load("angelina-wang/directional_bias_amplification")
 >>> results = bias_amp_metric.compute(references=[[0], [1], [1], [0], [0], [0], [0], [1]], predictions=[[1], [1], [1], [0], [0], [0], [0], [0]], attributes=[[0, 1], [0, 1], [0, 1], [1, 0], [1, 0], [1, 0], [1, 0], [1, 0]])
 >>> print(results)
 {'bias_amplification': 0.2667, 'disagg_bias_amplification': [[0.2], [0.3333]]}