updating with bedtime story code

app.py

@@ -1,13 +1,20 @@
 import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, TextDataset, DataCollatorForLanguageModeling, Trainer, TrainingArguments, pipeline
+from accelerate import Accelerator
+accelerator = Accelerator(cpu=True)
 
-def greet(name):
-    return "Hello " + name + "!!"
+# def greet(name):
+#     return "Hello " + name + "!!"
+
+tokenizer = accelerator.prepare(AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125m"))
+model = accelerator.prepare(AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-neo-125m"))
 
 def plex(input_text):    
-        mnputs = tokenizer(input_text, return_tensors='pt')
-        prediction = model.generate(mnputs['input_ids'], min_length=20, max_length=150, num_return_sequences=1)
-        lines = tokenizer.decode(prediction[0]).splitlines()
-        return lines[0]
+    mnputs = tokenizer(input_text, return_tensors='pt')
+    prediction = model.generate(mnputs['input_ids'], min_length=20, max_length=150, num_return_sequences=1)
+    lines = tokenizer.decode(prediction[0]).splitlines()
+    return lines[0]
 
 iface=gr.Interface(
     fn=plex,