Upload lrzjason_Anything2Real_2601_0.txt with huggingface_hub

lrzjason_Anything2Real_2601_0.txt

@@ -0,0 +1,47 @@
+```CODE: 
+import torch
+from diffusers import DiffusionPipeline
+from diffusers.utils import load_image
+
+# switch to "mps" for apple devices
+pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511", dtype=torch.bfloat16, device_map="cuda")
+pipe.load_lora_weights("lrzjason/Anything2Real_2601")
+
+prompt = "Turn this cat into a dog"
+input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
+
+image = pipe(image=input_image, prompt=prompt).images[0]
+```
+
+ERROR: 
+Traceback (most recent call last):
+  File "/tmp/lrzjason_Anything2Real_2601_0NaAdR6.py", line 28, in <module>
+    pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511", dtype=torch.bfloat16, device_map="cuda")
+  File "/tmp/.cache/uv/environments-v2/da51cd39aee6b3c5/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/da51cd39aee6b3c5/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1021, 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/da51cd39aee6b3c5/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 876, in load_sub_model
+    loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
+  File "/tmp/.cache/uv/environments-v2/da51cd39aee6b3c5/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/da51cd39aee6b3c5/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1296, in from_pretrained
+    ) = cls._load_pretrained_model(
+        ~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        model,
+        ^^^^^^
+    ...<13 lines>...
+        is_parallel_loading_enabled=is_parallel_loading_enabled,
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/da51cd39aee6b3c5/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1635, in _load_pretrained_model
+    _caching_allocator_warmup(model, expanded_device_map, dtype, hf_quantizer)
+    ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/da51cd39aee6b3c5/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 751, in _caching_allocator_warmup
+    _ = torch.empty(warmup_elems, dtype=dtype, device=device, requires_grad=False)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 38.05 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_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)