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https://github.com/comfyanonymous/ComfyUI.git
synced 2026-01-11 06:40:48 +08:00
Include Kijai fp8 nodes. LoRAs are not supported by nf4
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@ -424,6 +424,8 @@ KNOWN_UNET_MODELS: Final[KnownDownloadables] = KnownDownloadables([
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HuggingFile("ByteDance/Hyper-SD", "Hyper-SDXL-1step-Unet-Comfyui.fp16.safetensors"),
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HuggingFile("black-forest-labs/FLUX.1-schnell", "flux1-schnell.safetensors"),
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HuggingFile("black-forest-labs/FLUX.1-dev", "flux1-dev.safetensors"),
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HuggingFile("Kijai/flux-fp8", "flux1-dev-fp8.safetensors"),
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HuggingFile("Kijai/flux-fp8", "flux1-schnell-fp8.safetensors"),
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], folder_name="diffusion_models")
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KNOWN_CLIP_MODELS: Final[KnownDownloadables] = KnownDownloadables([
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@ -386,7 +386,7 @@ class ModelPatcher(ModelManageable):
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logging.debug("loaded partially {} {} {}".format(lowvram_model_memory / (1024 * 1024), mem_counter / (1024 * 1024), patch_counter))
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self._memory_measurements.model_lowvram = True
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else:
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logging.info("loaded completely {} {} {}".format(lowvram_model_memory / (1024 * 1024), mem_counter / (1024 * 1024), full_load))
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logging.debug("loaded completely {} {} {}".format(lowvram_model_memory / (1024 * 1024), mem_counter / (1024 * 1024), full_load))
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self._memory_measurements.model_lowvram = False
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if full_load:
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self.model.to(device_to)
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@ -61,6 +61,8 @@ def copy_quant_state(state: QuantState, device: torch.device = None) -> QuantSta
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class ForgeParams4bit(Params4bit):
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def to(self, *args, **kwargs):
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if 'copy' in kwargs:
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kwargs.pop('copy')
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device, dtype, non_blocking, convert_to_format = torch._C._nn._parse_to(*args, **kwargs)
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if device is not None and device.type == "cuda" and not self.bnb_quantized:
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return self._quantize(device)
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@ -179,7 +181,7 @@ class CheckpointLoaderNF4:
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def load_checkpoint(self, ckpt_name):
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if not has_bitsandbytes:
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raise BitsAndBytesNotFoundError(f"Because your platform is {platform.platform()}, bitsandbytes is not installed, so this cannot be executed")
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raise BitsAndBytesNotFoundError(f"bitsandbytes is not installed, so {CheckpointLoaderNF4.__name__} cannot be executed")
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ckpt_path = get_or_download("checkpoints", ckpt_name)
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out = comfy.sd.load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, embedding_directory=get_folder_paths("embeddings"), model_options={"custom_operations": OPS})
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return out[:3]
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@ -10,7 +10,8 @@ sentencepiece
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peft>=0.10.0
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torchinfo
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safetensors>=0.4.2
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bitsandbytes>=0.43.0 ;platform_system == 'Linux' or platform_system == 'Windows'
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bitsandbytes>=0.43.0 ;platform_system != 'Darwin'
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bitsandbytes ;platform_system == 'Darwin'
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aiohttp>=3.8.4
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accelerate>=0.25.0
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pyyaml>=6.0
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