Upload Tongyi-MAI_Z-Image_0.txt with huggingface_hub

Tongyi-MAI_Z-Image_0.txt

@@ -0,0 +1,56 @@
+```CODE: 
+import torch
+from diffusers import DiffusionPipeline
+
+# switch to "mps" for apple devices
+pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image", dtype=torch.bfloat16, device_map="cuda")
+
+prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
+image = pipe(prompt).images[0]
+```
+
+ERROR: 
+Traceback (most recent call last):
+  File "/tmp/Tongyi-MAI_Z-Image_0zAHBfj.py", line 27, in <module>
+    pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image", dtype=torch.bfloat16, device_map="cuda")
+  File "/tmp/.cache/uv/environments-v2/f1dba588cc269c5c/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn
+    return fn(*args, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/f1dba588cc269c5c/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/f1dba588cc269c5c/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/f1dba588cc269c5c/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn
+    return fn(*args, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/f1dba588cc269c5c/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/f1dba588cc269c5c/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1678, in _load_pretrained_model
+    offload_index, state_dict_index, _mismatched_keys, _error_msgs = load_fn(shard_file)
+                                                                     ~~~~~~~^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/f1dba588cc269c5c/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 367, in _load_shard_file
+    offload_index, state_dict_index = load_model_dict_into_meta(
+                                      ~~~~~~~~~~~~~~~~~~~~~~~~~^
+        model,
+        ^^^^^^
+    ...<9 lines>...
+        state_dict_folder=state_dict_folder,
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/f1dba588cc269c5c/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 307, in load_model_dict_into_meta
+    set_module_tensor_to_device(model, param_name, param_device, value=param, **set_module_kwargs)
+    ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/f1dba588cc269c5c/lib/python3.13/site-packages/accelerate/utils/modeling.py", line 343, in set_module_tensor_to_device
+    new_value = value.to(device, non_blocking=non_blocking)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 58.00 MiB. GPU 0 has a total capacity of 22.03 GiB of which 5.12 MiB is free. Including non-PyTorch memory, this process has 22.02 GiB memory in use. Of the allocated memory 21.79 GiB is allocated by PyTorch, and 47.36 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)