Upload SG161222_SPARK.Chroma_preview_0.txt with huggingface_hub
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SG161222_SPARK.Chroma_preview_0.txt
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```CODE:
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from diffusers import DiffusionPipeline
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pipe = DiffusionPipeline.from_pretrained("SG161222/SPARK.Chroma_preview")
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prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
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image = pipe(prompt).images[0]
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```
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ERROR:
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Traceback (most recent call last):
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File "/tmp/SG161222_SPARK.Chroma_preview_0BMrkkI.py", line 18, in <module>
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pipe = DiffusionPipeline.from_pretrained("SG161222/SPARK.Chroma_preview")
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File "/tmp/.cache/uv/environments-v2/99f0e6eb04c48392/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
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return fn(*args, **kwargs)
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File "/tmp/.cache/uv/environments-v2/99f0e6eb04c48392/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1025, 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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...<21 lines>...
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quantization_config=quantization_config,
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)
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File "/tmp/.cache/uv/environments-v2/99f0e6eb04c48392/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 778, in load_sub_model
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raise ValueError(
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...<2 lines>...
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)
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ValueError: The component <class 'transformers.models.t5.tokenization_t5._LazyModule.__getattr__.<locals>.Placeholder'> of <class 'diffusers.pipelines.chroma.pipeline_chroma.ChromaPipeline'> 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']}.
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