minor fix

README.md

@@ -20,7 +20,7 @@ When loading SemScore, you can choose any pre-trained encoder-only model uploade
 
 ```python
 import evaluate
-semscore = evaluate.load("semscore", "model_name")
+semscore = evaluate.load("aynetdia/semscore", "model_name")
 ```
 
 SemScore takes 2 mandatory arguments in order to calculate the final score:

semscore.py

@@ -71,14 +71,11 @@ class SemScore(evaluate.Metric):
             inputs_description=_KWARGS_DESCRIPTION,
             # This defines the format of each prediction and reference
             features=datasets.Features({
-                'predictions': datasets.Value('int64'),
-                'references': datasets.Value('int64'),
+                'predictions': datasets.Value('string'),
+                'references': datasets.Value('string'),
             }),
-            # Homepage of the module for documentation
-            homepage="http://module.homepage",
-            # Additional links to the codebase or references
-            codebase_urls=["http://github.com/path/to/codebase/of/new_module"],
-            reference_urls=["http://path.to.reference.url/new_module"]
+            # Additional link to the reference
+            reference_urls=["https://arxiv.org/abs/2401.17072"]
         )
 
     def _download_and_prepare(self, dl_manager):