Upload black-forest-labs_FLUX.1-schnell_1.txt with huggingface_hub

black-forest-labs_FLUX.1-schnell_1.txt

@@ -0,0 +1,43 @@
+```CODE: 
+import torch
+from diffusers import DiffusionPipeline
+
+# switch to "mps" for apple devices
+pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", 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/black-forest-labs_FLUX.1-schnell_1XZxUeL.py", line 27, in <module>
+    pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", dtype=torch.bfloat16, device_map="cuda")
+  File "/tmp/.cache/uv/environments-v2/e32bfabdbd53d898/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/e32bfabdbd53d898/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1025, 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/e32bfabdbd53d898/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 860, in load_sub_model
+    loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
+  File "/tmp/.cache/uv/environments-v2/e32bfabdbd53d898/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/e32bfabdbd53d898/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1288, in from_pretrained
+    ) = cls._load_pretrained_model(
+        ~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        model,
+        ^^^^^^
+    ...<13 lines>...
+        is_parallel_loading_enabled=is_parallel_loading_enabled,
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/e32bfabdbd53d898/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1537, in _load_pretrained_model
+    _caching_allocator_warmup(model, expanded_device_map, dtype, hf_quantizer)
+    ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/e32bfabdbd53d898/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 754, in _caching_allocator_warmup
+    _ = torch.empty(warmup_elems, dtype=dtype, device=device, requires_grad=False)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 22.15 GiB. GPU 0 has a total capacity of 22.03 GiB of which 3.77 GiB is free. Including non-PyTorch memory, this process has 18.25 GiB memory in use. Of the allocated memory 18.06 GiB is allocated by PyTorch, and 17.48 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)