ariG23498 HF Staff commited on
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Upload black-forest-labs_FLUX.1-Kontext-dev_1.txt with huggingface_hub

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black-forest-labs_FLUX.1-Kontext-dev_1.txt CHANGED
@@ -14,7 +14,7 @@ image = pipe(image=input_image, prompt=prompt).images[0]
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  ERROR:
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  Traceback (most recent call last):
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- File "/tmp/black-forest-labs_FLUX.1-Kontext-dev_1rIMizY.py", line 26, in <module>
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  pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda")
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  File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
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  return fn(*args, **kwargs)
@@ -26,30 +26,21 @@ Traceback (most recent call last):
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  )
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  File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 860, 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/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/transformers/tokenization_utils_base.py", line 2097, in from_pretrained
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- return cls._from_pretrained(
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- ~~~~~~~~~~~~~~~~~~~~^
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- resolved_vocab_files,
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- ^^^^^^^^^^^^^^^^^^^^^
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- ...<9 lines>...
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- **kwargs,
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- ^^^^^^^^^
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- )
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- ^
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- File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/transformers/tokenization_utils_base.py", line 2343, in _from_pretrained
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- tokenizer = cls(*init_inputs, **init_kwargs)
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- File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/transformers/models/t5/tokenization_t5_fast.py", line 119, in __init__
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- super().__init__(
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- ~~~~~~~~~~~~~~~~^
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- vocab_file=vocab_file,
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- ^^^^^^^^^^^^^^^^^^^^^^
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- ...<7 lines>...
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- **kwargs,
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- ^^^^^^^^^
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  )
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  ^
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- File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/transformers/tokenization_utils_fast.py", line 108, in __init__
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- raise ValueError(
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- ...<2 lines>...
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- )
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- ValueError: Cannot instantiate this tokenizer from a slow version. If it's based on sentencepiece, make sure you have sentencepiece installed.
 
 
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  ERROR:
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  Traceback (most recent call last):
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+ File "/tmp/black-forest-labs_FLUX.1-Kontext-dev_1eNdKbL.py", line 28, in <module>
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  pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda")
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  File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/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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  )
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  File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 860, 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/ca96a1cdc2ecd6c7/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/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1288, 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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+ ...<13 lines>...
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+ is_parallel_loading_enabled=is_parallel_loading_enabled,
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+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 
 
 
 
 
 
 
 
 
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  )
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  ^
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+ File "/tmp/.cache/uv/environments-v2/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1537, 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/ca96a1cdc2ecd6c7/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 754, 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 22.17 GiB. GPU 0 has a total capacity of 22.03 GiB of which 3.64 GiB is free. Including non-PyTorch memory, this process has 18.38 GiB memory in use. Of the allocated memory 18.20 GiB is allocated by PyTorch, and 1.79 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)