Remove unused __init__ method and related code

The __init__ patching never worked due to timing (CrossEncoder instance
is created before module is loaded). Model loading happens in to_device()
instead. Also removed unused 'types' import.

modeling_zeranker.py

@@ -3,8 +3,6 @@ from sentence_transformers import CrossEncoder as _CE
 import math
 import logging
 from typing import cast, Any
-import types
-
 
 import torch
 from transformers.configuration_utils import PretrainedConfig
@@ -116,26 +114,6 @@ def load_model(
     return tokenizer, model
 
 
-# Store the original __init__ method
-_original_init = _CE.__init__
-
-
-def __init__(self, *args: Any, **kwargs: Any) -> None:
-    logger.info("Initializing CrossEncoder with eager model loading")
-    # Call the original CrossEncoder __init__ first
-    _original_init(self, *args, **kwargs)
-
-    # Load the model immediately on instantiation
-    logger.info("Loading model on instantiation (no lazy loading)")
-    self.inner_tokenizer, self.inner_model = load_model(global_device)
-    self.inner_model.eval()
-    self.inner_model.gradient_checkpointing_disable()
-    self.inner_yes_token_id = self.inner_tokenizer.encode(
-        "Yes", add_special_tokens=False
-    )[0]
-    logger.info(f"CrossEncoder initialization complete. Yes token ID: {self.inner_yes_token_id}")
-
-
 def predict(
     self,
     query_documents: list[tuple[str, str]] | None = None,
@@ -247,7 +225,6 @@ def to_device(self: _CE, new_device: torch.device) -> None:
         logger.info(f"Model loaded successfully. Yes token ID: {self.inner_yes_token_id}")
 
 
-_CE.__init__ = __init__
 _CE.predict = predict
 _CE.to = to_device