Readme update

README.md

@@ -42,7 +42,7 @@ Thus in binary classification, the count of true negatives is
 At minimum, this metric requires predictions and references as inputs.
 
 ```python
->>> cfm_metric = evaluate.load("confusion_matrix")
+>>> cfm_metric = evaluate.load("BucketHeadP65/confusion_matrix")
 >>> results = cfm_metric.compute(references=[1, 2, 3, 2, 1, 1, 0, 2], predictions=[1, 0, 3, 2, 2, 1, 0, 3])
 >>> print(results)
 {'confusion_matrix': [[1, 0, 0, 0], [0, 2, 1, 0], [1, 0, 1, 1], [0, 0, 0, 1]]}