Update README.md

README.md

@@ -13,20 +13,18 @@ This leads to what seems to be a slightly worse performance (42.8 vs 43.? on the
 To use this model, first clone the huggingface repo
 
 ```
+git clone https://huggingface.co/naver/trecdl22-crossencoder-rankT53b-repro
 
 ```
 
+And then we suggest loading it like follows:
 
 ```
 import torch
 from transformers import T5EncoderModel
 
 class T5EncoderRerank(torch.nn.Module):
-    def __init__(self, model_type_or_dir,fp16=False, bf16=False):
-        """
-        model_type_or_dir is either the name of a pre-trained model (e.g. bert-base-uncased), or the path to
-        directory containing model weights, vocab etc.
-        """
+    def __init__(self, model_type_or_dir):
         super().__init__()
         self.model = T5EncoderModel.from_pretrained(model_type_or_dir)
         self.config = self.model.config