cpu torch

app.py

@@ -25,13 +25,13 @@ with open('family_labels.pkl', 'rb') as filefam:
 
 tokenizerfam = AutoTokenizer.from_pretrained("facebook/esm2_t12_35M_UR50D") #facebook/esm2_t33_650M_UR50D
 
-device = 'cuda' if torch.cuda.is_available() else 'cpu'
+device = 'cpu'
 device
 
 modelfam = EsmForSequenceClassification.from_pretrained("facebook/esm2_t12_35M_UR50D", num_labels=len(yfam.classes_))
 modelfam = modelfam.to('cpu')
 
-modelfam.load_state_dict(torch.load("family.pth"))
+modelfam.load_state_dict(torch.load("family.pth", map_location=torch.device('cpu')))
 modelfam.eval()
 
 x_testfam = ["""MAEVLRTLAGKPKCHALRPMILFLIMLVLVLFGYGVLSPRSLMPGSLERGFCMAVREPDH