.

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import transformers
 from model_config import PragFormerConfig
-from model import PragFormer
+from model import Pragformer
 from simpletransformers.classification import ClassificationModel, ClassificationArgs
 import torch
 import json
@@ -11,9 +11,9 @@ deep_scc_model_args = ClassificationArgs(num_train_epochs=10,max_seq_length=300,
 deep_scc_model = ClassificationModel("roberta", "NTUYG/DeepSCC-RoBERTa", num_labels=19, args=deep_scc_model_args, use_cuda=False)
 
 pragformer_config = PragFormerConfig.from_pretrained("Pragformer/PragFormer", trust_remote_code=True)
-pragformer = PragFormer.from_pretrained("Pragformer/PragFormer", config=pragformer_config, trust_remote_code=True)
-pragformer_private = PragFormerConfig.from_pretrained("Pragformer/PragFormer_private", config=pragformer_config, trust_remote_code=True)
-pragformer_reduction = PragFormerConfig.from_pretrained("Pragformer/PragFormer_reduction", config=pragformer_config, trust_remote_code=True)
+pragformer = Pragformer.from_pretrained("Pragformer/PragFormer", config=pragformer_config, trust_remote_code=True)
+pragformer_private = Pragformer.from_pretrained("Pragformer/PragFormer_private", config=pragformer_config, trust_remote_code=True)
+pragformer_reduction = Pragformer.from_pretrained("Pragformer/PragFormer_reduction", config=pragformer_config, trust_remote_code=True)
 
 
 #Event Listeners

model.py

@@ -5,7 +5,7 @@ from model_config import PragFormerConfig
 
 
 
-class BERT_Arch(PreTrainedModel): #(BertPreTrainedModel):
+class Pragformer(PreTrainedModel): #(BertPreTrainedModel):
     config_class = PragFormerConfig
 
     def __init__(self, config):