Update model.py

model.py

@@ -35,15 +35,7 @@ def load_embedder_and_tokenizer(name: str) -> Tuple[
         transformers.PreTrainedTokenizer
 ]:
     if name.startswith("nomic") or (name == "bert-base-uncased"):
-        from cde.lib.nomic_bert import NomicBertModel
-        if name.endswith("--from-scratch"):
-            name = name.replace("--from-scratch", "")
-            config = transformers.AutoConfig.from_pretrained(name, trust_remote_code=True)
-            model = NomicBertModel._from_config(config)
-        else:
-            model = NomicBertModel.from_pretrained(
-                name, add_pooling_layer=False
-            )
+        model = transfromers.AutoModel.from_pretrained(name)
         tokenizer = transformers.AutoTokenizer.from_pretrained(name)
     elif name in ["gtr-base", "gtr_base"]:
         model = transformers.AutoModel.from_pretrained(