Upload Lightricks_LTX-Video_0.txt with huggingface_hub

Lightricks_LTX-Video_0.txt

@@ -0,0 +1,35 @@
+```CODE: 
+import torch
+from diffusers import DiffusionPipeline
+from diffusers.utils import load_image, export_to_video
+
+# switch to "mps" for apple devices
+pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-Video", dtype=torch.bfloat16, device_map="cuda")
+pipe.to("cuda")
+
+prompt = "A man with short gray hair plays a red electric guitar."
+image = load_image(
+    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
+)
+
+output = pipe(image=image, prompt=prompt).frames[0]
+export_to_video(output, "output.mp4")
+```
+
+ERROR: 
+Traceback (most recent call last):
+  File "/tmp/Lightricks_LTX-Video_0QlFD3T.py", line 26, 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)
+  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1025, in from_pretrained
+    loaded_sub_model = load_sub_model(
+        library_name=library_name,
+    ...<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>...
+    )
+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']}.