Add device and remove dead verbose argument.

meaningbert.py

@@ -66,7 +66,7 @@ MeaningBERT metric for assessing meaning preservation between sentences.
 Args:
     documents (list of str): Document sentences.
     simplifications (list of str): Simplification sentences (same number of element as documents).
-    verbose (bool): Turn on intermediate status update.
+    device (str): Device to use for model inference. By default, set to "cuda".
 
 Returns:
     score: the meaning score between two sentences in alist format respecting the order of the documents and 
@@ -77,7 +77,7 @@ Examples:
 
     >>> documents = ["hello there", "general kenobi"]
     >>> simplifications = ["hello there", "general kenobi"]
-    >>> meaning_bert = evaluate.load("davebulaval/meaningbert")
+    >>> meaning_bert = evaluate.load("davebulaval/meaningbert", device="cuda:0")
     >>> results = meaning_bert.compute(documents=documents, simplifications=simplifications)
 """
 
@@ -112,7 +112,7 @@ class MeaningBERT(evaluate.Metric):
         self,
         documents: List,
         simplifications: List,
-        verbose: bool = False,
+        device: str = "cuda",
     ) -> Dict:
         assert len(documents) == len(
             simplifications
@@ -126,7 +126,7 @@ class MeaningBERT(evaluate.Metric):
 
         # We load the MeaningBERT pretrained model
         scorer = AutoModelForSequenceClassification.from_pretrained(
-            "davebulaval/MeaningBERT"
+            "davebulaval/MeaningBERT", device_map=device
         )
         scorer.eval()