Update tasks/text.py

tasks/text.py

@@ -3,7 +3,7 @@ from datetime import datetime
 from datasets import load_dataset
 from sklearn.metrics import accuracy_score
 import random
-import dill
+import cloudpickle
 from .utils.evaluation import TextEvaluationRequest
 from .utils.emissions import tracker, clean_emissions_data, get_space_info
 from .utils.predict import predict 
@@ -73,7 +73,7 @@ async def evaluate_text(request: TextEvaluationRequest):
     current_dir = os.path.dirname(current_file_path)
 
     with open(os.path.join(current_dir,"tfidf_vectorizer2.pkl"), "rb") as tfidf_file:
-        tfidf_vectorizer = dill.load(tfidf_file)
+        tfidf_vectorizer = cloudpickle.load(tfidf_file)
     
 
     # Make predictions using the loaded model