another test ?

app.py

@@ -1,17 +1,17 @@
 import gradio as gr
-#from transformers import pipeline
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import pipeline
+#from transformers import AutoModelForCausalLM, AutoTokenizer
 
 #model = AutoModel.from_pretrained("kolbeins/model")  
-#pipeline = pipeline(task="text-generation", model="kolbeins/model")
-model = AutoModelForCausalLM.from_pretrained("kolbeins/model")
-tokenizer = AutoTokenizer.from_pretrained("kolbeins/model")
+pipeline = pipeline(task="text-generation", model="kolbeins/model")
+#model = AutoModelForCausalLM.from_pretrained("kolbeins/model")
+#tokenizer = AutoTokenizer.from_pretrained("kolbeins/model")
 
 def chat(input_txt):
-    # response = pipeline(input_txt)
-    inputs = tokenizer(input_txt, return_tensors="pt")
-    outputs = model.generate(inputs["input_ids"], max_length=150, num_return_sequences=1)
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    response = pipeline(input_txt)
+    #inputs = tokenizer(input_txt, return_tensors="pt")
+    #outputs = model.generate(inputs["input_ids"], max_length=150, num_return_sequences=1)
+    #response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response
 
 demo = gr.Interface(fn=chat, inputs="text", outputs="text")