runtime error

Exit code: 1. Reason: 12 19:31:18,883 INFO Audio-only mode: freed video components, saved 0.0GB VRAM 2026-07-12 19:31:18,884 INFO PromptEncoder (warm): 31.4s 2026-07-12 19:31:18,936 INFO AudioConditioner (warm): 0.1s Traceback (most recent call last): File "/app/app.py", line 37, in <module> tts = TTSServer( checkpoint=PATHS["transformer"], ...<5 lines>... bnb_4bit=True, # unsloth Gemma is pre-quantized ) File "/app/src/inference_server.py", line 149, in __init__ self._load_all() ~~~~~~~~~~~~~~^^ File "/app/src/inference_server.py", line 218, in _load_all self._velocity_model = builder.build(device=self.device, dtype=self.dtype).to(self.device).eval() ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/app/ltx2/ltx_core/loader/single_gpu_model_builder.py", line 111, in build model_state_dict = self.load_sd(model_paths, sd_ops=self.model_sd_ops, registry=self.registry, device=device) File "/app/ltx2/ltx_core/loader/single_gpu_model_builder.py", line 88, in load_sd state_dict = self.model_loader.load(paths, sd_ops=sd_ops, device=device) File "/app/ltx2/ltx_core/loader/sft_loader.py", line 66, in load return self.weight_loader.load(path, sd_ops, device) ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^ File "/app/ltx2/ltx_core/loader/sft_loader.py", line 36, in load value = f.get_tensor(name).to(device=device, non_blocking=True, copy=False) ~~~~~~~~~~~~^^^^^^ torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 14.19 MiB is free. Process 74622 has 14.72 GiB memory in use. Of the allocated memory 13.91 GiB is allocated by PyTorch, and 729.25 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

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