Update app.py

app.py

@@ -1,14 +1,14 @@
 
 #MBART FINE TUNE
-import os
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+#import os
+#os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
 
 import gradio as gr
-import tensorflow as tf
-import torch 
+#import tensorflow as tf
+#import torch 
 
 import sentencepiece
-from transformers import MBartTokenizer, TFMBartForConditionalGeneration
+from transformers import MBartTokenizer, MBartForConditionalGeneration
 
 def run_model(input_text, 
               min_length,
@@ -16,13 +16,13 @@ def run_model(input_text,
               length_penalty):
 
     #MBART Transformer 
-    mbart_model =  TFMBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50",from_pt=True)
+    mbart_model =  MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50")#,from_pt=True)
     mbart_tokenizer = MBartTokenizer.from_pretrained("facebook/mbart-large-50")
 
     #encode input to vector
     input_text = str(input_text)
     input_text = ' '.join(input_text.split()) # hapus white space 
-    input_tokenized = mbart_tokenizer.encode(input_text, return_tensors='tf')
+    input_tokenized = mbart_tokenizer.encode(input_text, return_tensors='np')
         
     #generate input
     summary_ids = mbart_model.generate(input_tokenized,