remove device handling

meaningbert.py

@@ -67,7 +67,6 @@ MeaningBERT metric for assessing meaning preservation between sentences.
 Args:
     predictions (list of str): Predictions sentences.
     references (list of str): References sentences (same number of element as predictions).
-    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 predictions and 
@@ -78,7 +77,7 @@ Examples:
 
     >>> references = ["hello there", "general kenobi"]
     >>> predictions = ["hello there", "general kenobi"]
-    >>> meaning_bert = evaluate.load("davebulaval/meaningbert", device="cuda:0")
+    >>> meaning_bert = evaluate.load("davebulaval/meaningbert")
     >>> results = meaning_bert.compute(predictions=predictions, references=references)
 """
 
@@ -113,7 +112,6 @@ class MeaningBERT(evaluate.Metric):
         self,
         predictions: List,
         references: List,
-        device: str = "cuda",
     ) -> Dict:
         assert len(references) == len(
             predictions
@@ -125,7 +123,7 @@ class MeaningBERT(evaluate.Metric):
 
         # We load the MeaningBERT pretrained model
         scorer = AutoModelForSequenceClassification.from_pretrained(
-            "davebulaval/MeaningBERT", device_map=device
+            "davebulaval/MeaningBERT"
         )
         scorer.eval()
 
@@ -140,7 +138,7 @@ class MeaningBERT(evaluate.Metric):
                 truncation=True,
                 padding=True,
                 return_tensors="pt",
-            ).to(device)
+            )
 
             with filter_logging_context():
                 # We process the text