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Upload Lightricks_LTX-2_0.txt with huggingface_hub

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  1. Lightricks_LTX-2_0.txt +22 -16
Lightricks_LTX-2_0.txt CHANGED
@@ -18,27 +18,33 @@ export_to_video(output, "output.mp4")
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  ERROR:
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  Traceback (most recent call last):
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- File "/tmp/Lightricks_LTX-2_0TjSKOc.py", line 28, in <module>
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  pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-2", dtype=torch.bfloat16, device_map="cuda")
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  File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn
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  return fn(*args, **kwargs)
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- File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 829, in from_pretrained
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- cached_folder = cls.download(
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- pretrained_model_name_or_path,
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- ...<14 lines>...
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- **kwargs,
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  )
 
 
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  File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn
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  return fn(*args, **kwargs)
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- File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1637, in download
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- custom_components, folder_names = _get_custom_components_and_folders(
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- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
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- pretrained_model_name, config_dict, filenames, variant
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- ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 
 
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  )
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  ^
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- File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 1071, in _get_custom_components_and_folders
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- raise ValueError(
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- f"{candidate_file} as defined in `model_index.json` does not exist in {pretrained_model_name} and is not a module in 'diffusers/pipelines'."
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- )
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- ValueError: connectors/ltx2.py as defined in `model_index.json` does not exist in Lightricks/LTX-2 and is not a module in 'diffusers/pipelines'.
 
 
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  ERROR:
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  Traceback (most recent call last):
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+ File "/tmp/Lightricks_LTX-2_0PRXjbm.py", line 28, in <module>
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  pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-2", dtype=torch.bfloat16, device_map="cuda")
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  File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn
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  return fn(*args, **kwargs)
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+ File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1049, in from_pretrained
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+ loaded_sub_model = load_sub_model(
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+ library_name=library_name,
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+ ...<22 lines>...
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+ quantization_config=quantization_config,
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  )
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+ File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 885, in load_sub_model
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+ loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
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  File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn
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  return fn(*args, **kwargs)
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+ File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1312, in from_pretrained
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+ ) = cls._load_pretrained_model(
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+ ~~~~~~~~~~~~~~~~~~~~~~~~~~^
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+ model,
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+ ^^^^^^
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+ ...<14 lines>...
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+ disable_mmap=disable_mmap,
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+ ^^^^^^^^^^^^^^^^^^^^^^^^^^
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  )
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  ^
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+ File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1652, in _load_pretrained_model
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+ _caching_allocator_warmup(model, expanded_device_map, dtype, hf_quantizer)
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+ ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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+ File "/tmp/.cache/uv/environments-v2/e8822e4ae31fc8f1/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 758, in _caching_allocator_warmup
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+ _ = torch.empty(warmup_elems, dtype=dtype, device=device, requires_grad=False)
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+ torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 35.16 GiB. GPU 0 has a total capacity of 22.03 GiB of which 16.48 GiB is free. Including non-PyTorch memory, this process has 5.54 GiB memory in use. Of the allocated memory 5.33 GiB is allocated by PyTorch, and 31.36 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)