Upload ServiceNow-AI_Apriel-1.6-15b-Thinker_0.txt with huggingface_hub

ServiceNow-AI_Apriel-1.6-15b-Thinker_0.txt

@@ -17,7 +17,7 @@ pipe(text=messages)
 
 ERROR: 
 Traceback (most recent call last):
-  File "/tmp/ServiceNow-AI_Apriel-1.6-15b-Thinker_0DZnYXF.py", line 26, in <module>
+  File "/tmp/ServiceNow-AI_Apriel-1.6-15b-Thinker_0ZCJBo4.py", line 26, in <module>
     pipe = pipeline("image-text-to-text", model="ServiceNow-AI/Apriel-1.6-15b-Thinker")
   File "/tmp/.cache/uv/environments-v2/10e48a7117c25b66/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1229, in pipeline
     return pipeline_class(model=model, framework=framework, task=task, **kwargs)
@@ -56,4 +56,4 @@ Traceback (most recent call last):
         ^^^^^^^^^^^^^
     )
     ^
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 140.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 88.69 MiB is free. Process 49908 has 22.21 GiB memory in use. Of the allocated memory 21.96 GiB is allocated by PyTorch, and 126.00 KiB 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 140.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 88.69 MiB is free. Process 1576798 has 22.21 GiB memory in use. Of the allocated memory 21.96 GiB is allocated by PyTorch, and 126.00 KiB 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)