runtime error

Space not ready. Reason: Error, exitCode: 1, message: None

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/home/user/.local/lib/python3.8/site-packages/diffusers/models/attention.py:424: UserWarning: Could not enable memory efficient attention. Make sure xformers is installed correctly and a GPU is available: torch.cuda.is_available() should be True but is False. xformers' memory efficient attention is only available for GPU 
  warnings.warn(
You have disabled the safety checker for <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .
Pipelines loaded with `torch_dtype=torch.float16` cannot run with `cpu` device. It is not recommended to move them to `cpu` as running them will fail. Please make sure to use an accelerator to run the pipeline in inference, due to the lack of support for`float16` operations on this device in PyTorch. Please, remove the `torch_dtype=torch.float16` argument, or use another device for inference.
Pipelines loaded with `torch_dtype=torch.float16` cannot run with `cpu` device. It is not recommended to move them to `cpu` as running them will fail. Please make sure to use an accelerator to run the pipeline in inference, due to the lack of support for`float16` operations on this device in PyTorch. Please, remove the `torch_dtype=torch.float16` argument, or use another device for inference.
Pipelines loaded with `torch_dtype=torch.float16` cannot run with `cpu` device. It is not recommended to move them to `cpu` as running them will fail. Please make sure to use an accelerator to run the pipeline in inference, due to the lack of support for`float16` operations on this device in PyTorch. Please, remove the `torch_dtype=torch.float16` argument, or use another device for inference.
╭───────────────────── Traceback (most recent call last) ──────────────────────╮
│ /home/user/app/app.py:30 in <module>                                         │
│                                                                              │
│    27 scheduler = EulerDiscreteScheduler.from_pretrained(repo_id, subfolder= │
│    28 pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.fl │
│    29 pipe = pipe.to(device)                                                 │
│ ❱  30 pipe.enable_xformers_memory_efficient_attention()                      │
│    31                                                                        │
│    32 #If you have duplicated this Space or is running locally, you can remo │
│    33 word_list_dataset = load_dataset("stabilityai/word-list", data_files=" │
│                                                                              │
│ /home/user/.local/lib/python3.8/site-packages/diffusers/pipelines/stable_dif │
│ fusion/pipeline_stable_diffusion.py:146 in                                   │
│ enable_xformers_memory_efficient_attention                                   │
│                                                                              │
│   143 │   │   Warning: When Memory Efficient Attention and Sliced attention  │
│   144 │   │   is used.                                                       │
│   145 │   │   """                                                            │
│ ❱ 146 │   │   self.unet.set_use_memory_efficient_attention_xformers(True)    │
│   147 │                                                                      │
│   148 │   def disable_xformers_memory_efficient_attention(self):             │
│   149 │   │   r"""                                                           │
│                                                                              │
│ /home/user/.local/lib/python3.8/site-packages/diffusers/models/unet_2d_condi │
│ tion.py:244 in set_use_memory_efficient_attention_xformers                   │
│                                                                              │
│   241 │   def set_use_memory_efficient_attention_xformers(self, use_memory_e │
│   242 │   │   for block in self.down_blocks:                                 │
│   243 │   │   │   if hasattr(block, "attentions") and block.attentions is no │
│ ❱ 244 │   │   │   │   block.set_use_memory_efficient_attention_xformers(use_ │
│   245 │   │                                                                  │
│   246 │   │   self.mid_block.set_use_memory_efficient_attention_xformers(use │
│   247                                                                        │
│                                                                              │
│ /home/user/.local/lib/python3.8/site-packages/diffusers/models/unet_2d_block │
│ s.py:613 in set_use_memory_efficient_attention_xformers                      │
│                                                                              │
│    610 │                                                                     │
│    611 │   def set_use_memory_efficient_attention_xformers(self, use_memory_ │
│    612 │   │   for attn in self.attentions:                                  │
│ ❱  613 │   │   │   attn._set_use_memory_efficient_attention_xformers(use_mem │
│    614 │                                                                     │
│    615 │   def forward(self, hidden_states, temb=None, encoder_hidden_states │
│    616 │   │   output_states = ()                                            │
│                                                                              │
│ /home/user/.local/lib/python3.8/site-packages/diffusers/models/attention.py: │
│ 245 in _set_use_memory_efficient_attention_xformers                          │
│                                                                              │
│   242 │                                                                      │
│   243 │   def _set_use_memory_efficient_attention_xformers(self, use_memory_ │
│   244 │   │   for block in self.transformer_blocks:                          │
│ ❱ 245 │   │   │   block._set_use_memory_efficient_attention_xformers(use_mem │
│   246                                                                        │
│   247                                                                        │
│   248 class AttentionBlock(nn.Module):                                       │
│                                                                              │
│ /home/user/.local/lib/python3.8/site-packages/diffusers/models/attention.py: │
│ 442 in _set_use_memory_efficient_attention_xformers                          │
│                                                                              │
│   439 │   │   │   │   name="xformers",                                       │
│   440 │   │   │   )                                                          │
│   441 │   │   elif not torch.cuda.is_available():                            │
│ ❱ 442 │   │   │   raise ValueError(                                          │
│   443 │   │   │   │   "torch.cuda.is_available() should be True but is False │
│   444 │   │   │   │   " available for GPU "                                  │
│   445 │   │   │   )                                                          │
╰──────────────────────────────────────────────────────────────────────────────╯
ValueError: torch.cuda.is_available() should be True but is False. xformers' 
memory efficient attention is only available for GPU