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Only apply gemma quant config to gemma model for newbie. (#11436)

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comfyanonymous 2025-12-19 22:02:43 -08:00 committed by GitHub
parent 4c432c11ed
commit fb478f679a
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2 changed files with 6 additions and 1 deletions
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5
comfy/text_encoders/lumina2.py
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@ -33,6 +33,11 @@ class Gemma2_2BModel(sd1_clip.SDClipModel):
class Gemma3_4BModel(sd1_clip.SDClipModel):
def __init__(self, device="cpu", layer="hidden", layer_idx=-2, dtype=None, attention_mask=True, model_options={}):
llama_quantization_metadata = model_options.get("llama_quantization_metadata", None)
if llama_quantization_metadata is not None:
model_options = model_options.copy()
model_options["quantization_metadata"] = llama_quantization_metadata
super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config={}, dtype=dtype, special_tokens={"start": 2, "pad": 0}, layer_norm_hidden_state=False, model_class=comfy.text_encoders.llama.Gemma3_4B, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options)
class LuminaModel(sd1_clip.SD1ClipModel):

2
comfy/text_encoders/newbie.py
View File

@ -57,6 +57,6 @@ def te(dtype_llama=None, llama_quantization_metadata=None):
def __init__(self, device="cpu", dtype=None, model_options={}):
if llama_quantization_metadata is not None:
model_options = model_options.copy()
model_options["quantization_metadata"] = llama_quantization_metadata
model_options["llama_quantization_metadata"] = llama_quantization_metadata
super().__init__(dtype_gemma=dtype_llama, device=device, dtype=dtype, model_options=model_options)
return NewBieTEModel_