Rename the class and add a parameter, 'dimension' to support both versions

model_api.py

@@ -6,17 +6,18 @@ from mteb import DRESModel
 from tqdm import tqdm
 
 
-class ModelV1(DRESModel):
-    def __init__(self, url: str, instruction: Optional[str] = None, batch_size: int = 128, **kwargs) -> None:
+class SionicEmbeddingModel(DRESModel):
+    def __init__(self, url: str, instruction: Optional[str] = None, batch_size: int = 128, dimension: int = 2048, **kwargs) -> None:
         self.url = url
         self.instruction = instruction
         self.batch_size = batch_size
+        self.dimension = dimension
 
     def get_embeddings(self, queries: List[str]) -> np.ndarray:
         return np.asarray(
             requests.post(self.url, json={'inputs': queries}).json()['embedding'],
             dtype=np.float32,
-        ).reshape(len(queries), 2048)
+        ).reshape(len(queries), self.dimension)
 
     def encode_queries(self, queries: List[str], **kwargs) -> np.ndarray:
         return self.encode([f'{self.instruction}{query}' for query in queries])
@@ -38,3 +39,4 @@ class ModelV1(DRESModel):
             ],
             axis=0,
         )
+