bug fixing

requirements.txt

@@ -10,3 +10,4 @@ requests>=2.31.0
 librosa==0.10.2.post1
 torch>=2.5
 transformers>=4.48
+numpy>=2.2

tasks/text.py

@@ -2,6 +2,7 @@ from fastapi import APIRouter
 from datetime import datetime
 from datasets import load_dataset
 from sklearn.metrics import accuracy_score
+import numpy as np
 import random
 import torch
 from transformers import AutoConfig, AutoModelForSequenceClassification, AutoTokenizer
@@ -39,6 +40,7 @@ def bert_model(test_dataset):
     else:
         device = torch.device('cpu')
     print('device:', device)
+    model = model.to(device)
     test_encoding = tokenizer(
         texts,
         truncation=True,
@@ -54,7 +56,8 @@ def bert_model(test_dataset):
         outputs = model(test_input_ids, test_attention_mask)
         print('End of model run.')
         predictions = torch.argmax(outputs.logits, dim=1)
-
+        predictions = predictions.cpu().numpy()
+        
     print('End of my code block.')
     return predictions