CodeCow/stable-diffusion-webui-forge
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Haoming 2025-10-28 15:51:41 +08:00
parent 23c35442cd
commit 2bbffe9ceb
1 changed files with 17 additions and 10 deletions
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27
modules_forge/packages/huggingface_guess/model_list.py
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@ -320,17 +320,18 @@ class Chroma(FluxSchnell):
supported_inference_dtypes = [torch.bfloat16, torch.float16, torch.float32]
def clip_target(self, state_dict={}):
result = {}
pref = self.text_encoder_key_prefix[0]
text_encoder_key_prefix = ["text_encoders.", "cond_stage_model."]
if "{}t5xxl.transformer.encoder.final_layer_norm.weight".format(pref) in state_dict:
result["t5xxl"] = "text_encoder"
def clip_target(self, state_dict: dict):
for pref in self.text_encoder_key_prefix:
if "{}t5xxl.transformer.encoder.final_layer_norm.weight".format(pref) in state_dict:
return {"t5xxl": "text_encoder"}
elif "{}t5xxl.transformer.encoder.final_layer_norm.qweight".format(pref) in state_dict:
return {"t5xxl": "text_encoder"}
elif "{}t5xxl.transformer.encoder.final_layer_norm.qweight".format(pref) in state_dict:
result["t5xxl"] = "text_encoder"
return result
def process_vae_state_dict(self, state_dict):
replace_prefix = {"first_stage_model.": "vae."}
return utils.state_dict_prefix_replace(state_dict, replace_prefix)
class Lumina2(BASE):
@ -358,7 +359,13 @@ class Lumina2(BASE):
unet_target = "transformer"
def clip_target(self, state_dict={}):
return {"gemma2_2b": "text_encoder"}
pref = self.text_encoder_key_prefix[0]
if "{}gemma2_2b.transformer.model.embed_tokens.weight".format(pref) in state_dict:
state_dict.pop("{}gemma2_2b.logit_scale".format(pref), None)
state_dict.pop("{}spiece_model".format(pref), None)
return {"gemma2_2b.transformer": "text_encoder"}
else:
return {"gemma2_2b": "text_encoder"}
class WAN21_T2V(BASE):