Rename LLAMATokenizer to SPieceTokenizer.

comfy/text_encoders/aura_t5.py

 from comfy import sd1_clip
-from .llama_tokenizer import LLAMATokenizer
+from .spiece_tokenizer import SPieceTokenizer
 import comfy.text_encoders.t5
 import os
 
@@ -11,7 +11,7 @@ class PT5XlModel(sd1_clip.SDClipModel):
 class PT5XlTokenizer(sd1_clip.SDTokenizer):
     def __init__(self, embedding_directory=None):
         tokenizer_path = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_tokenizer"), "tokenizer.model")
-        super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=LLAMATokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1)
+        super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=SPieceTokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1)
 
 class AuraT5Tokenizer(sd1_clip.SD1Tokenizer):
     def __init__(self, embedding_directory=None):

comfy/text_encoders/llama_tokenizer.py → comfy/text_encoders/spiece_tokenizer.py

 import os
 
-class LLAMATokenizer:
+class SPieceTokenizer:
     @staticmethod
     def from_pretrained(path):
-        return LLAMATokenizer(path)
+        return SPieceTokenizer(path)
 
     def __init__(self, tokenizer_path):
         import sentencepiece