diff --git a/src/peft/tuners/adalora.py b/src/peft/tuners/adalora.py
index aff877adac..e0140d6acc 100644
--- a/src/peft/tuners/adalora.py
+++ b/src/peft/tuners/adalora.py
@@ -80,7 +80,7 @@ class AdaLoraModel(LoraModel):
                 peft_type="ADALORA", task_type="SEQ_2_SEQ_LM", r=8, lora_alpha=32, target_modules=["q", "v"],
                 lora_dropout=0.01,
             )
-        >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base") >>> model = AdaLoraModel(config, model)
+        >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base") >>> model = AdaLoraModel(model, config, "default")
 
     **Attributes**:
         - **model** ([`transformers.PreTrainedModel`]) -- The model to be adapted.
diff --git a/src/peft/tuners/lora.py b/src/peft/tuners/lora.py
index a3b97cad3a..af062ddf48 100644
--- a/src/peft/tuners/lora.py
+++ b/src/peft/tuners/lora.py
@@ -123,11 +123,10 @@ class LoraModel(torch.nn.Module):
     Example:
 
         ```py
-        >>> from transformers import AutoModelForSeq2SeqLM, LoraConfig
+        >>> from transformers import AutoModelForSeq2SeqLM
         >>> from peft import LoraModel, LoraConfig
 
         >>> config = LoraConfig(
-        ...     peft_type="LORA",
         ...     task_type="SEQ_2_SEQ_LM",
         ...     r=8,
         ...     lora_alpha=32,
@@ -136,7 +135,7 @@ class LoraModel(torch.nn.Module):
         ... )
 
         >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
-        >>> lora_model = LoraModel(config, model)
+        >>> lora_model = LoraModel(model, config, "default")
         ```
 
         ```py