asd

app.py

@@ -9,14 +9,15 @@ from transformers import AutoModelWithLMHead, AutoTokenizer, pipeline, set_seed
 import gradio as grad
 from diffusers import StableDiffusionPipeline
 
+tokenizer = AutoTokenizer.from_pretrained("shahp7575/gpt2-horoscopes")
+model = AutoModelWithLMHead.from_pretrained("shahp7575/gpt2-horoscopes")
+
 def fn(sign, cat):
-    category = "career"
     sign = "scorpio"
 
     prompt = f"<|category|> {cat} <|horoscope|> {sign}"
 
-    tokenizer = AutoTokenizer.from_pretrained("shahp7575/gpt2-horoscopes")
-    model = AutoModelWithLMHead.from_pretrained("shahp7575/gpt2-horoscopes")
+    
 
     prompt_encoded = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0)