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More flexible long clip support.

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Add clip g long clip support.

Text encoder refactor.

Support llama models with different vocab sizes.
This commit is contained in:
comfyanonymous
2025-04-15 10:32:21 -04:00
parent 8a438115fb
commit 3e8155f7a3
17 changed files with 95 additions and 66 deletions
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2
comfy/text_encoders/lumina2.py
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@@ -6,7 +6,7 @@ import comfy.text_encoders.llama
class Gemma2BTokenizer(sd1_clip.SDTokenizer):
def __init__(self, embedding_directory=None, tokenizer_data={}):
tokenizer = tokenizer_data.get("spiece_model", None)
super().__init__(tokenizer, pad_with_end=False, embedding_size=2304, embedding_key='gemma2_2b', tokenizer_class=SPieceTokenizer, has_end_token=False, pad_to_max_length=False, max_length=99999999, min_length=1, tokenizer_args={"add_bos": True, "add_eos": False})
super().__init__(tokenizer, pad_with_end=False, embedding_size=2304, embedding_key='gemma2_2b', tokenizer_class=SPieceTokenizer, has_end_token=False, pad_to_max_length=False, max_length=99999999, min_length=1, tokenizer_args={"add_bos": True, "add_eos": False}, tokenizer_data=tokenizer_data)
def state_dict(self):
return {"spiece_model": self.tokenizer.serialize_model()}