feat: 简化代码，节省空间

app.py

@@ -2,12 +2,13 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 from transformers import pipeline
 
-tokenizer = AutoTokenizer.from_pretrained("cerebras/Cerebras-GPT-13B")
+# tokenizer = AutoTokenizer.from_pretrained("cerebras/Cerebras-GPT-13B")
 model = AutoModelForCausalLM.from_pretrained("cerebras/Cerebras-GPT-13B")
 
 text = "Generative AI is "
 
-pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+# pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+pipe = pipeline("text-generation", model=model)
 
 def greet(speech):
     generated_text = pipe(speech, max_length=50, do_sample=False, no_repeat_ngram_size=2)[0]