Upload Lightricks_LTX-Video_0.txt with huggingface_hub

Lightricks_LTX-Video_0.txt

@@ -18,7 +18,7 @@ export_to_video(output, "output.mp4")
 
 ERROR: 
 Traceback (most recent call last):
-  File "/tmp/Lightricks_LTX-Video_0QlFD3T.py", line 26, in <module>
+  File "/tmp/Lightricks_LTX-Video_0PrdE45.py", line 28, in <module>
     pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-Video", dtype=torch.bfloat16, device_map="cuda")
   File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
     return fn(*args, **kwargs)
@@ -28,8 +28,23 @@ Traceback (most recent call last):
     ...<21 lines>...
         quantization_config=quantization_config,
     )
-  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 778, in load_sub_model
-    raise ValueError(
-    ...<2 lines>...
+  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 860, in load_sub_model
+    loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
+  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
+    return fn(*args, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1288, in from_pretrained
+    ) = cls._load_pretrained_model(
+        ~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        model,
+        ^^^^^^
+    ...<13 lines>...
+        is_parallel_loading_enabled=is_parallel_loading_enabled,
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     )
-ValueError: The component <class 'transformers.models.t5.tokenization_t5._LazyModule.__getattr__.<locals>.Placeholder'> of <class 'diffusers.pipelines.ltx.pipeline_ltx.LTXPipeline'> cannot be loaded as it does not seem to have any of the loading methods defined in {'ModelMixin': ['save_pretrained', 'from_pretrained'], 'SchedulerMixin': ['save_pretrained', 'from_pretrained'], 'DiffusionPipeline': ['save_pretrained', 'from_pretrained'], 'OnnxRuntimeModel': ['save_pretrained', 'from_pretrained'], 'PreTrainedTokenizer': ['save_pretrained', 'from_pretrained'], 'PreTrainedTokenizerFast': ['save_pretrained', 'from_pretrained'], 'PreTrainedModel': ['save_pretrained', 'from_pretrained'], 'FeatureExtractionMixin': ['save_pretrained', 'from_pretrained'], 'ProcessorMixin': ['save_pretrained', 'from_pretrained'], 'ImageProcessingMixin': ['save_pretrained', 'from_pretrained'], 'ORTModule': ['save_pretrained', 'from_pretrained']}.
+    ^
+  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1537, in _load_pretrained_model
+    _caching_allocator_warmup(model, expanded_device_map, dtype, hf_quantizer)
+    ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 754, in _caching_allocator_warmup
+    _ = torch.empty(warmup_elems, dtype=dtype, device=device, requires_grad=False)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 3.58 GiB. GPU 0 has a total capacity of 22.03 GiB of which 2.49 GiB is free. Including non-PyTorch memory, this process has 19.53 GiB memory in use. Of the allocated memory 19.33 GiB is allocated by PyTorch, and 27.19 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)