try again

app.py

@@ -8,11 +8,16 @@ model_id = "AverageBusinessUser/aidapal"
 filename = "aidapal-8k.Q4_K_M.gguf"
 
 print("Downloading model")
-pipe = pipeline(task="text-generation", model=model_id, gguf_file=filename, device_map="auto")
 
-#torch_dtype = torch.float32 # could be torch.float16 or torch.bfloat16 too
-#tokenizer = AutoTokenizer.from_pretrained(model_id, gguf_file=filename)
-#model = AutoModelForCausalLM.from_pretrained(model_id, gguf_file=filename, torch_dtype=torch_dtype)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    gguf_file=filename,
+    device_map="auto"
+)
+
+# Then create the pipeline with the model and tokenizer
+pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer)
 
 @spaces.GPU
 def greet(name):