fix transformers

app.py

@@ -32,6 +32,8 @@ from operator import itemgetter
 
 import gradio as gr
 
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
 global df
 bearer_token = 'AAAAAAAAAAAAAAAAAAAAACEigwEAAAAACoP8KHJYLOKCL4OyB9LEPV00VB0%3DmyeDROUvw4uipHwvbPPfnTuY0M9ORrLuXrMvcByqZhwo3SUc4F'
 client = tweepy.Client(bearer_token=bearer_token)
@@ -392,11 +394,10 @@ def full_lda(df):
     return top_tweets
 
 def topic_summarization(topic_groups):
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    
 
-    model = T5ForConditionalGeneration.from_pretrained("Michau/t5-base-en-generate-headline")
-    tokenizer = T5Tokenizer.from_pretrained("Michau/t5-base-en-generate-headline")
-    model = model.to(device)
+    tokenizer = AutoTokenizer.from_pretrained("Michau/t5-base-en-generate-headline")
+    model = AutoModelForSeq2SeqLM.from_pretrained("Michau/t5-base-en-generate-headline")
     translator = Translator()
 
     headlines = []
@@ -410,8 +411,8 @@ def topic_summarization(topic_groups):
         max_len = 256
 
         encoding = tokenizer.encode_plus(text, return_tensors = "pt")
-        input_ids = encoding["input_ids"].to(device)
-        attention_masks = encoding["attention_mask"].to(device)
+        input_ids = encoding["input_ids"]
+        attention_masks = encoding["attention_mask"]
 
         beam_outputs = model.generate(
             input_ids = input_ids,