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Support loading flux 2 klein checkpoints saved with SaveCheckpoint. (#12033)

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comfyanonymous 2026-01-22 15:20:48 -08:00 committed by GitHub
parent 0fd1b78736
commit 09a2e67151
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2 changed files with 22 additions and 6 deletions
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20
comfy/supported_models.py
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@ -771,10 +771,24 @@ class Flux2(Flux):
return out
def clip_target(self, state_dict={}):
return None # TODO
pref = self.text_encoder_key_prefix[0]
t5_detect = comfy.text_encoders.sd3_clip.t5_xxl_detect(state_dict, "{}t5xxl.transformer.".format(pref))
return supported_models_base.ClipTarget(comfy.text_encoders.flux.FluxTokenizer, comfy.text_encoders.flux.flux_clip(**t5_detect))
detect = comfy.text_encoders.hunyuan_video.llama_detect(state_dict, "{}qwen3_4b.transformer.".format(pref))
if len(detect) > 0:
detect["model_type"] = "qwen3_4b"
return supported_models_base.ClipTarget(comfy.text_encoders.flux.KleinTokenizer, comfy.text_encoders.flux.klein_te(**detect))
detect = comfy.text_encoders.hunyuan_video.llama_detect(state_dict, "{}qwen3_8b.transformer.".format(pref))
if len(detect) > 0:
detect["model_type"] = "qwen3_8b"
return supported_models_base.ClipTarget(comfy.text_encoders.flux.KleinTokenizer8B, comfy.text_encoders.flux.klein_te(**detect))
detect = comfy.text_encoders.hunyuan_video.llama_detect(state_dict, "{}mistral3_24b.transformer.".format(pref))
if len(detect) > 0:
if "{}mistral3_24b.transformer.model.layers.39.post_attention_layernorm.weight".format(pref) not in state_dict:
detect["pruned"] = True
return supported_models_base.ClipTarget(comfy.text_encoders.flux.Flux2Tokenizer, comfy.text_encoders.flux.flux2_te(**detect))
return None
class GenmoMochi(supported_models_base.BASE):
unet_config = {

8
comfy/text_encoders/hunyuan_video.py
View File

@ -10,9 +10,11 @@ import comfy.utils
def llama_detect(state_dict, prefix=""):
out = {}
t5_key = "{}model.norm.weight".format(prefix)
if t5_key in state_dict:
out["dtype_llama"] = state_dict[t5_key].dtype
norm_keys = ["{}model.norm.weight".format(prefix), "{}model.layers.0.input_layernorm.weight".format(prefix)]
for norm_key in norm_keys:
if norm_key in state_dict:
out["dtype_llama"] = state_dict[norm_key].dtype
break
quant = comfy.utils.detect_layer_quantization(state_dict, prefix)
if quant is not None: