diff --git a/comfy/text_encoders/lt.py b/comfy/text_encoders/lt.py index e5964e42b..130ebaeae 100644 --- a/comfy/text_encoders/lt.py +++ b/comfy/text_encoders/lt.py @@ -36,10 +36,10 @@ class LTXAVGemmaTokenizer(sd1_clip.SD1Tokenizer): class Gemma3_12BModel(sd1_clip.SDClipModel): def __init__(self, device="cpu", layer="all", layer_idx=None, dtype=None, attention_mask=True, model_options={}): - llama_scaled_fp8 = model_options.get("gemma_scaled_fp8", None) - if llama_scaled_fp8 is not None: + llama_quantization_metadata = model_options.get("llama_quantization_metadata", None) + if llama_quantization_metadata is not None: model_options = model_options.copy() - model_options["scaled_fp8"] = llama_scaled_fp8 + 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_12B, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options) @@ -119,12 +119,12 @@ class LTXAVTEModel(torch.nn.Module): return self.load_state_dict(sdo, strict=False) -def ltxav_te(dtype_llama=None, llama_scaled_fp8=None): +def ltxav_te(dtype_llama=None, llama_quantization_metadata=None): class LTXAVTEModel_(LTXAVTEModel): def __init__(self, device="cpu", dtype=None, model_options={}): - if llama_scaled_fp8 is not None and "llama_scaled_fp8" not in model_options: + if llama_quantization_metadata is not None: model_options = model_options.copy() - model_options["llama_scaled_fp8"] = llama_scaled_fp8 + model_options["llama_quantization_metadata"] = llama_quantization_metadata if dtype_llama is not None: dtype = dtype_llama super().__init__(dtype_llama=dtype_llama, device=device, dtype=dtype, model_options=model_options)