Update app.py

app.py

@@ -11,13 +11,7 @@ max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!
 dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
 load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
 
-model, tokenizer = AutoModelForCausalLM.from_pretrained(
-    model_name = "Qwen/Qwen2-1.5B",
-    max_seq_length = max_seq_length,
-    dtype = dtype,
-    load_in_4bit = load_in_4bit
-)
-
+model, tokenizer = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-1.5B", max_seq_length = max_seq_length, dtype = dtype, load_in_4bit = load_in_4bit)
 model = PeftModel.from_pretrained(model, "RandomNameAnd6/Phi-3-Mini-Dhar-Mann-Adapters-BOS")
 
 def generate_text(prompt):