fix(README): AutoModelForSequenceClassification example

README.md

@@ -88,7 +88,7 @@ You should fine-tune the model on labelled data unless you are using the model f
 
 ```python
 import torch
-from transformers import AutoModelForSequenceClassification, AutoModelForTokenClassification
+from transformers import AutoModelForSequenceClassification
 from peft import get_peft_model
 from peft.tuners.lora.config import LoraConfig
 
@@ -99,7 +99,7 @@ lora_config = LoraConfig(
     bias = "none",
     task_type = "SEQ_CLS"
   )
-model = AutoModel.from_pretrained(
+model = AutoModelForSequenceClassification.from_pretrained(
     "fdschmidt93/NLLB-LLM2Vec-Meta-Llama-31-8B-Instruct-mntp-unsup-simcse",
     trust_remote_code=True,
     torch_dtype=torch.bfloat16,