enjoy, im going to sleep

[MyCroniesSoft]

"negative_prompt": "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards", "infer_steps": 17, "target_video_length": 81, "target_width": 832, "target_height": 480, "self_attn_1_type": "flash_attn2", "cross_attn_1_type": "flash_attn2", "cross_attn_2_type": "flash_attn2", "seed": 2050392903, "enable_cfg": true, "sample_guide_scale": 5, "sample_shift": 5, "cpu_offload": false, "offload_granularity": "block", "offload_ratio": 1, "t5_offload_granularity": "model", "dit_quantized_ckpt": "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\int8", "mm_config": { "mm_type": "W-int8-channel-sym-A-int8-channel-sym-dynamic-Vllm" }, "fps": 16, "feature_caching": "NoCaching", "coefficients": [ -5784.54975374, 5449.50911966, -1811.16591783, 256.27178429, -13.02252404 ], "use_ret_steps": false, "teacache_thresh": 0.26, "t5_cpu_offload": false, "unload_modules": false, "t5_original_ckpt": "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\models_t5_umt5-xxl-enc-bf16.pth", "t5_quantized": false, "t5_quantized_ckpt": null, "t5_quant_scheme": "bf16", "clip_original_ckpt": null, "clip_quantized": true, "clip_quantized_ckpt": "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\int8\clip-int8.pth", "clip_quant_scheme": "int8", "vae_path": "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\int8\Wan2.1_VAE.pth", "use_tiling_vae": false, "use_tiny_vae": false, "tiny_vae_path": null, "lazy_load": false, "do_mm_calib": false, "parallel_attn_type": null, "parallel_vae": false, "max_area": false, "vae_stride": [ 4, 8, 8 ], "patch_size": [ 1, 2, 2 ], "lora_path": "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\loras\Wan2.2 - T2V - Missionary Sex - LOW 14B.safetensors", "strength_model": 1.0, "use_prompt_enhancer": false, "text_len": 512, "rotary_chunk": false, "rotary_chunk_size": 100, "clean_cuda_cache": false, "denoising_step_list": [ 1000, 750, 500, 250 ], "model_path": "Z:\Projects\wan2p_with_hun_and_vace\LightX2V", "cfg_parallel": false, "model_type": "i2v", "_class_name": "WanModel", "_diffusers_version": "0.30.0", "dim": 5120, "eps": 1e-06, "ffn_dim": 13824, "freq_dim": 256, "in_dim": 36, "num_heads": 40, "num_layers": 40, "out_dim": 16 } 2025-08-12 23:34:25.464 | INFO | lightx2v.models.runners.default_runner:init_modules:33 - Initializing runner modules... 2025-08-12 23:34:25.465 | INFO | lightx2v.models.networks.wan.model:_init_weights:180 - Loading model weights on rank 0... 2025-08-12 23:34:25.465 | INFO | lightx2v.models.networks.wan.model:_load_monolithic_ckpt:149 - ✅ Searching for monolithic checkpoints in: Z:\Projects\wan2p_with_hun_and_vace\LightX2V\int8 2025-08-12 23:34:25.466 | INFO | lightx2v.models.networks.wan.model:_load_monolithic_ckpt:161 - ✅ Found and loading HIGH model: Z:\Projects\wan2p_with_hun_and_vace\LightX2V\int8\high_noise_model.safetensors 2025-08-12 23:34:27.103 | INFO | lightx2v.models.networks.wan.model:_load_monolithic_ckpt:166 - ✅ Found and loading LOW model: Z:\Projects\wan2p_with_hun_and_vace\LightX2V\int8\low_noise_model.safetensors 2025-08-12 23:34:28.648 | INFO | lightx2v.utils.profiler:exit:29 - [Profile] Single GPU - Load models cost 3.185183 seconds Traceback (most recent call last): File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\gradio\queueing.py", line 626, in process_events response = await route_utils.call_process_api( File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\gradio\route_utils.py", line 350, in call_process_api output = await app.get_blocks().process_api( File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\gradio\blocks.py", line 2250, in process_api result = await self.call_function( File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\gradio\blocks.py", line 1757, in call_function prediction = await anyio.to_thread.run_sync( # type: ignore File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync return await get_async_backend().run_sync_in_worker_thread( File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\anyio_backends_asyncio.py", line 2476, in run_sync_in_worker_thread return await future File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\anyio_backends_asyncio.py", line 967, in run result = context.run(func, *args) File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\venv\lib\site-packages\gradio\utils.py", line 917, in wrapper response = f(*args, **kwargs) File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\app\gradio_demo.py", line 991, in run_inference runner = init_runner(config) File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\infer.py", line 32, in init_runner runner.init_modules() File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\models\runners\default_runner.py", line 35, in init_modules self.load_model() File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\utils\profiler.py", line 57, in sync_wrapper return func(*args, **kwargs) File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\models\runners\default_runner.py", line 62, in load_model self.model = self.load_transformer() File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\models\runners\wan\wan_runner.py", line 44, in load_transformer model = WanModel( File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\models\networks\wan\model.py", line 75, in init self._init_weights() File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\models\networks\wan\model.py", line 227, in _init_weights self.pre_weight.load(self.original_weight_dict) File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\common\modules\weight_module.py", line 19, in load module.load(weight_dict) File "Z:\Projects\wan2p_with_hun_and_vace\LightX2V\lightx2v\common\ops\conv\conv3d.py", line 37, in load self.weight = weight_dict[self.weight_name] KeyError: 'patch_embedding.weight'