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Make it easier to set a custom template for hunyuan video.

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comfyanonymous
2025-03-04 09:26:05 -05:00
parent 7c7c70c400
commit 65042f7d39
7 changed files with 13 additions and 10 deletions
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2
comfy/text_encoders/flux.py
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@@ -18,7 +18,7 @@ class FluxTokenizer:
self.clip_l = clip_l_tokenizer_class(embedding_directory=embedding_directory)
self.t5xxl = T5XXLTokenizer(embedding_directory=embedding_directory)
def tokenize_with_weights(self, text:str, return_word_ids=False):
def tokenize_with_weights(self, text:str, return_word_ids=False, **kwargs):
out = {}
out["l"] = self.clip_l.tokenize_with_weights(text, return_word_ids)
out["t5xxl"] = self.t5xxl.tokenize_with_weights(text, return_word_ids)

7
comfy/text_encoders/hunyuan_video.py
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@@ -41,11 +41,14 @@ class HunyuanVideoTokenizer:
self.llama_template = """<|start_header_id|>system<|end_header_id|>\n\nDescribe the video by detailing the following aspects: 1. The main content and theme of the video.2. The color, shape, size, texture, quantity, text, and spatial relationships of the objects.3. Actions, events, behaviors temporal relationships, physical movement changes of the objects.4. background environment, light, style and atmosphere.5. camera angles, movements, and transitions used in the video:<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n""" # 95 tokens
self.llama = LLAMA3Tokenizer(embedding_directory=embedding_directory, min_length=1)
def tokenize_with_weights(self, text:str, return_word_ids=False):
def tokenize_with_weights(self, text:str, return_word_ids=False, llama_template=None, **kwargs):
out = {}
out["l"] = self.clip_l.tokenize_with_weights(text, return_word_ids)
llama_text = "{}{}".format(self.llama_template, text)
if llama_template is None:
llama_text = "{}{}".format(self.llama_template, text)
else:
llama_text = "{}{}".format(llama_template, text)
out["llama"] = self.llama.tokenize_with_weights(llama_text, return_word_ids)
return out

2
comfy/text_encoders/hydit.py
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@@ -37,7 +37,7 @@ class HyditTokenizer:
self.hydit_clip = HyditBertTokenizer(embedding_directory=embedding_directory)
self.mt5xl = MT5XLTokenizer(tokenizer_data={"spiece_model": mt5_tokenizer_data}, embedding_directory=embedding_directory)
def tokenize_with_weights(self, text:str, return_word_ids=False):
def tokenize_with_weights(self, text:str, return_word_ids=False, **kwargs):
out = {}
out["hydit_clip"] = self.hydit_clip.tokenize_with_weights(text, return_word_ids)
out["mt5xl"] = self.mt5xl.tokenize_with_weights(text, return_word_ids)

2
comfy/text_encoders/sd3_clip.py
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@@ -43,7 +43,7 @@ class SD3Tokenizer:
self.clip_g = sdxl_clip.SDXLClipGTokenizer(embedding_directory=embedding_directory)
self.t5xxl = T5XXLTokenizer(embedding_directory=embedding_directory)
def tokenize_with_weights(self, text:str, return_word_ids=False):
def tokenize_with_weights(self, text:str, return_word_ids=False, **kwargs):
out = {}
out["g"] = self.clip_g.tokenize_with_weights(text, return_word_ids)
out["l"] = self.clip_l.tokenize_with_weights(text, return_word_ids)