Load models, corpus embeddings onto GPU device for text search, if available

- Pass device to load models onto from app state.
  - SentenceTransformer models accept device to load models onto during initialization
- Pass device to load corpus embeddings onto from app state

src/utils/helpers.py

@@ -41,17 +41,17 @@ def merge_dicts(priority_dict: dict, default_dict: dict):
     return merged_dict
 
 
-def load_model(model_name, model_dir, model_type):
+def load_model(model_name, model_dir, model_type, device:str=None):
     "Load model from disk or huggingface"
     # Construct model path
     model_path = join(model_dir, model_name.replace("/", "_")) if model_dir is not None else None
 
     # Load model from model_path if it exists there
     if model_path is not None and resolve_absolute_path(model_path).exists():
-        model = model_type(get_absolute_path(model_path))
+        model = model_type(get_absolute_path(model_path), device=device)
     # Else load the model from the model_name
     else:
-        model = model_type(model_name)
+        model = model_type(model_name, device=device)
         if model_path is not None:
             model.save(model_path)