Upload inclusionAI_Ling-mini-2.0_0.txt with huggingface_hub

inclusionAI_Ling-mini-2.0_0.txt

@@ -1,5 +1,5 @@
 Traceback (most recent call last):
-  File "/tmp/inclusionAI_Ling-mini-2.0_0PR3DRI.py", line 13, in <module>
+  File "/tmp/inclusionAI_Ling-mini-2.0_0t5zShr.py", line 13, in <module>
     pipe = pipeline("text-generation", model="inclusionAI/Ling-mini-2.0", trust_remote_code=True)
   File "/tmp/.cache/uv/environments-v2/21e4f0866aa2210b/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1230, in pipeline
     return pipeline_class(model=model, framework=framework, task=task, **kwargs)
@@ -9,7 +9,7 @@ Traceback (most recent call last):
   File "/tmp/.cache/uv/environments-v2/21e4f0866aa2210b/lib/python3.13/site-packages/transformers/pipelines/base.py", line 1044, in __init__
     self.model.to(self.device)
     ~~~~~~~~~~~~~^^^^^^^^^^^^^
-  File "/tmp/.cache/uv/environments-v2/21e4f0866aa2210b/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4459, in to
+  File "/tmp/.cache/uv/environments-v2/21e4f0866aa2210b/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4462, in to
     return super().to(*args, **kwargs)
            ~~~~~~~~~~^^^^^^^^^^^^^^^^^
   File "/tmp/.cache/uv/environments-v2/21e4f0866aa2210b/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1369, in to
@@ -38,4 +38,4 @@ Traceback (most recent call last):
         ^^^^^^^^^^^^^
     )
     ^
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 12.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 4.69 MiB is free. Process 27113 has 22.29 GiB memory in use. Of the allocated memory 22.05 GiB is allocated by PyTorch, and 1.86 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)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 12.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 4.69 MiB is free. Process 26304 has 22.29 GiB memory in use. Of the allocated memory 22.05 GiB is allocated by PyTorch, and 1.86 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)