Upload inclusionAI_Ling-lite-1.5-2507_0.txt with huggingface_hub

inclusionAI_Ling-lite-1.5-2507_0.txt

@@ -1,5 +1,5 @@
 Traceback (most recent call last):
-  File "/tmp/inclusionAI_Ling-lite-1.5-2507_0NJgMDR.py", line 13, in <module>
+  File "/tmp/inclusionAI_Ling-lite-1.5-2507_02LfHcc.py", line 13, in <module>
     pipe = pipeline("text-generation", model="inclusionAI/Ling-lite-1.5-2507", trust_remote_code=True)
   File "/tmp/.cache/uv/environments-v2/a07e8353e3325c3d/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1210, 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/a07e8353e3325c3d/lib/python3.13/site-packages/transformers/pipelines/base.py", line 1043, in __init__
     self.model.to(self.device)
     ~~~~~~~~~~~~~^^^^^^^^^^^^^
-  File "/tmp/.cache/uv/environments-v2/a07e8353e3325c3d/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4333, in to
+  File "/tmp/.cache/uv/environments-v2/a07e8353e3325c3d/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4341, in to
     return super().to(*args, **kwargs)
            ~~~~~~~~~~^^^^^^^^^^^^^^^^^
   File "/tmp/.cache/uv/environments-v2/a07e8353e3325c3d/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 20.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 14.69 MiB is free. Process 25641 has 22.28 GiB memory in use. Of the allocated memory 18.42 GiB is allocated by PyTorch, and 3.62 GiB 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 20.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 14.69 MiB is free. Process 25906 has 22.28 GiB memory in use. Of the allocated memory 18.42 GiB is allocated by PyTorch, and 3.62 GiB 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)