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Upload black-forest-labs_FLUX.2-dev_1.txt with huggingface_hub

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  1. black-forest-labs_FLUX.2-dev_1.txt +17 -38
black-forest-labs_FLUX.2-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.2-dev_15zNXYg.py", line 28, in <module>
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  pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-dev", dtype=torch.bfloat16, device_map="cuda")
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  File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn
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  return fn(*args, **kwargs)
@@ -26,42 +26,21 @@ Traceback (most recent call last):
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  )
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  File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 876, 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/d49ad6c613615895/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4109, in from_pretrained
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- load_info = cls._load_pretrained_model(model, state_dict, checkpoint_files, load_config)
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- File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4231, in _load_pretrained_model
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- convert_and_load_state_dict_in_model(
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- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
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- model=model,
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- ^^^^^^^^^^^^
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- ...<4 lines>...
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- disk_offload_index=disk_offload_index,
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- ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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- )
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- ^
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- File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/transformers/core_model_loading.py", line 1217, in convert_and_load_state_dict_in_model
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- realized_value, conversion_errors = mapping.convert(
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- ~~~~~~~~~~~~~~~^
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- first_param_name,
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- ^^^^^^^^^^^^^^^^^
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- ...<4 lines>...
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- conversion_errors=conversion_errors,
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- ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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  )
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  ^
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- File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/transformers/core_model_loading.py", line 696, in convert
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- collected_tensors = self.materialize_tensors()
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- File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/transformers/core_model_loading.py", line 671, in materialize_tensors
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- tensors = [future.result() for future in tensors]
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- ~~~~~~~~~~~~~^^
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- File "/usr/lib/python3.13/concurrent/futures/_base.py", line 456, in result
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- return self.__get_result()
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- ~~~~~~~~~~~~~~~~~^^
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- File "/usr/lib/python3.13/concurrent/futures/_base.py", line 401, in __get_result
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- raise self._exception
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- File "/usr/lib/python3.13/concurrent/futures/thread.py", line 59, in run
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- result = self.fn(*self.args, **self.kwargs)
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- File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/transformers/core_model_loading.py", line 818, in _job
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- return _materialize_copy(tensor, device, dtype)
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- File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/transformers/core_model_loading.py", line 807, in _materialize_copy
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- tensor = tensor.to(device=device, dtype=dtype)
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- torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 320.00 MiB. GPU 0 has a total capacity of 22.03 GiB of which 265.12 MiB is free. Including non-PyTorch memory, this process has 21.77 GiB memory in use. Of the allocated memory 21.45 GiB is allocated by PyTorch, and 143.64 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)
 
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  ERROR:
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  Traceback (most recent call last):
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+ File "/tmp/black-forest-labs_FLUX.2-dev_1tKRE1v.py", line 28, in <module>
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  pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-dev", dtype=torch.bfloat16, device_map="cuda")
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  File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/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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  )
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  File "/tmp/.cache/uv/environments-v2/d49ad6c613615895/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 876, 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/d49ad6c613615895/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/d49ad6c613615895/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1296, 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/d49ad6c613615895/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1635, 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/d49ad6c613615895/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 751, 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 60.02 GiB. GPU 0 has a total capacity of 22.03 GiB of which 21.84 GiB is free. Including non-PyTorch memory, this process has 186.00 MiB memory in use. Of the allocated memory 0 bytes is allocated by PyTorch, and 0 bytes 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)