Upload google_translategemma-12b-it_1.txt with huggingface_hub

google_translategemma-12b-it_1.txt

@@ -17,7 +17,7 @@ pipe(text=messages)
 
 ERROR: 
 Traceback (most recent call last):
-  File "/tmp/google_translategemma-12b-it_1E6F4TF.py", line 26, in <module>
+  File "/tmp/google_translategemma-12b-it_1JqqM0G.py", line 26, in <module>
     pipe = pipeline("image-text-to-text", model="google/translategemma-12b-it")
   File "/tmp/.cache/uv/environments-v2/b56b4359def432d5/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1028, in pipeline
     return pipeline_class(model=model, task=task, **kwargs)
@@ -56,4 +56,4 @@ Traceback (most recent call last):
         ^^^^^^^^^^^^^
     )
     ^
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 114.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 78.69 MiB is free. Process 3572802 has 22.22 GiB memory in use. Of the allocated memory 21.75 GiB is allocated by PyTorch, and 233.66 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_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 114.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 78.69 MiB is free. Process 42353 has 22.22 GiB memory in use. Of the allocated memory 21.75 GiB is allocated by PyTorch, and 233.66 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)