fix: another approach

app.py

@@ -1,22 +1,21 @@
 import gradio as gr
 import spaces
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline
 import logging
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)
 
-# Load model and tokenizer
+# Load model and tokenizer using pipeline
 logging.info("Loading model and tokenizer...")
 model_name = "speakleash/Bielik-11B-v2.3-Instruct"
-model = AutoModelForCausalLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+pipe = pipeline("text-generation", model=model_name)
 
 
 @spaces.GPU
 def process_text(input_text):
-    inputs = tokenizer(input_text, return_tensors="pt")
-    outputs = model(**inputs)
+    messages = [{"role": "user", "content": input_text}]
+    outputs = pipe(messages)
     # Process outputs as needed
     return outputs