nodes/kijai-ComfyUI-WanVideoWrapper
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Allow using GGUF Multi/InfiniteTalk models

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kijai
2025-08-19 17:48:58 +03:00
parent 345c286c86
commit b6d4c172f0
2 changed files with 11 additions and 21 deletions
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multitalk/nodes.py
+8 -16
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@@ -12,9 +12,7 @@ class MultiTalkModelLoader:
def INPUT_TYPES(s):
return {
"required": {
"model": (folder_paths.get_filename_list("diffusion_models"), {"tooltip": "These models are loaded from the 'ComfyUI/models/diffusion_models' -folder",}),
"base_precision": (["fp32", "bf16", "fp16"], {"default": "fp16"}),
"model": (folder_paths.get_filename_list("unet_gguf") + folder_paths.get_filename_list("diffusion_models"), {"tooltip": "These models are loaded from the 'ComfyUI/models/diffusion_models' -folder",}),
},
}
@@ -23,18 +21,16 @@ class MultiTalkModelLoader:
FUNCTION = "loadmodel"
CATEGORY = "WanVideoWrapper"
def loadmodel(self, model, base_precision):
def loadmodel(self, model, base_precision=None):
from .multitalk import AudioProjModel
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
base_dtype = {"fp8_e4m3fn": torch.float8_e4m3fn, "fp8_e4m3fn_fast": torch.float8_e4m3fn, "bf16": torch.bfloat16, "fp16": torch.float16, "fp16_fast": torch.float16, "fp32": torch.float32}[base_precision]
model_path = folder_paths.get_full_path_or_raise("diffusion_models", model)
sd = load_torch_file(model_path, device=offload_device, safe_load=True)
audio_proj_keys = [k for k in sd.keys() if "audio_proj" in k]
audio_proj_sd = {k.replace("audio_proj.", ""): sd.pop(k) for k in audio_proj_keys}
if model_path.endswith(".gguf"):
from diffusers.models.model_loading_utils import load_gguf_checkpoint
sd = load_gguf_checkpoint(model_path)
else:
sd = load_torch_file(model_path, device=offload_device, safe_load=True)
audio_window=5
intermediate_dim=512
@@ -52,18 +48,14 @@ class MultiTalkModelLoader:
context_tokens=context_tokens,
norm_output_audio=norm_output_audio,
)
#fantasytalking_proj_model.load_state_dict(sd, strict=False)
for name, param in multitalk_proj_model.named_parameters():
set_module_tensor_to_device(multitalk_proj_model, name, device=offload_device, dtype=base_dtype, value=audio_proj_sd[name])
multitalk = {
"proj_model": multitalk_proj_model,
"sd": sd,
"is_gguf": model_path.endswith(".gguf")
}
return (multitalk,)
def loudness_norm(audio_array, sr=16000, lufs=-23):
try: