Remove torch dependency and more generic dim0 workaround

Remove torch dependency from hf.py
Make workaround for dimension zero values of token_ids
more generic to handle every token, not just newlines.

modeling/inference_models/hf.py

@@ -1,7 +1,6 @@
 import os
 from typing import Optional
 from transformers import AutoConfig
-import torch
 
 import utils
 import koboldai_settings
@@ -41,16 +40,24 @@ class HFInferenceModel(InferenceModel):
             original_decode = type(self.tokenizer.tokenizer).decode
             def decode_wrapper(self, token_ids, *args, **kwargs):
                 first = None
-                dim0 = False
+                # Note, the code below that wraps single-value token_ids in a list
+                # is to work around this wonky behavior:
+                #   >>> t.decode(13)
+                #   '<0x0A>'
+                #   >>> t.decode([13])
+                #   '\n'
+                # Not doing this causes token streaming to receive <0x0A> characters
+                # instead of newlines.
                 if isinstance(token_ids, int):
                     first = token_ids
-                    dim0 = True
-                elif isinstance(token_ids, torch.Tensor):
+                    token_ids = [first]
+                elif hasattr(token_ids, 'dim'): # Check for e.g. torch.Tensor
                     # Tensors don't support the Python standard of 'empty is False'
-                    # and the special case of dimension 0 tensors also needs to be handled separately.
+                    # and the special case of dimension 0 tensors also needs to be
+                    # handled separately.
                     if token_ids.dim() == 0:
                         first = int(token_ids.item())
-                        dim0 = True
+                        token_ids = [first]
                     elif len(token_ids) > 0:
                         first = int(token_ids[0])
                 elif token_ids:
@@ -58,14 +65,6 @@ class HFInferenceModel(InferenceModel):
                 result = original_decode(self, token_ids, *args, **kwargs)
                 if first is not None and first in has_prefix_space:
                     result = " " + result
-                if dim0:
-                    # Work around this wonky behavior:
-                    #   >>> t.decode(13)
-                    #   '<0x0A>'
-                    #   >>> t.decode([13])
-                    #   '\n'
-                    # Not doing this causes token streaming to receive <0x0A> characters instead of newlines.
-                    result = result.replace('<0x0A>', '\n')
                 return result
             # GenericTokenizer overrides __setattr__ so we need to use object.__setattr__ to bypass it
             object.__setattr__(self.tokenizer, 'decode', decode_wrapper.__get__(self.tokenizer))