Add **kwargs to Transformer to avoid issues when ST adds new arguments

custom_st.py

@@ -1,4 +1,5 @@
 import json
+import logging
 import os
 from io import BytesIO
 from typing import Any, Dict, List, Optional, Tuple, Union
@@ -7,6 +8,8 @@ import torch
 from torch import nn
 from transformers import AutoConfig, AutoModel, AutoTokenizer
 
+logger = logging.getLogger(__name__)
+
 
 class Transformer(nn.Module):
     """Huggingface AutoModel to generate token embeddings.
@@ -40,6 +43,7 @@ class Transformer(nn.Module):
         cache_dir: str = None,
         do_lower_case: bool = False,
         tokenizer_name_or_path: str = None,
+        **kwargs,
     ) -> None:
         super().__init__()
         self.config_keys = ["max_seq_length", "do_lower_case"]
@@ -51,6 +55,11 @@ class Transformer(nn.Module):
         if config_args is None:
             config_args = {}
 
+        if kwargs.get("backend", "torch") != "torch":
+            logger.warning(
+                f'"jinaai/jina-embeddings-v3" is currently not compatible with the {kwargs["backend"]} backend. '
+                'Continuing with the "torch" backend.'
+            )
         
         self.config = AutoConfig.from_pretrained(model_name_or_path, **config_args, cache_dir=cache_dir)