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This FutureWarning appears to be new in torch 2.4.0
.venv\Lib\site-packages\stanza\models\tokenize\trainer.py:85: FutureWarning: You are using torch.loadwithweights_only=False(the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value forweights_onlywill be flipped toTrue. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=Truefor any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. checkpoint = torch.load(filename, lambda storage, loc: storage)
The text was updated successfully, but these errors were encountered:
@janpeterka Add those lines to the argos-translate bin file, before 'cli.main()'. Mine lives in the '/home/me/.local/bin/' directory (after having followed normal pip installation). Just copypasta those lines into the file and save. It'll look something like this when its good:
This FutureWarning appears to be new in torch 2.4.0
.venv\Lib\site-packages\stanza\models\tokenize\trainer.py:85: FutureWarning: You are using
torch.loadwith
weights_only=False(the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for
weights_onlywill be flipped to
True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via
torch.serialization.add_safe_globals. We recommend you start setting
weights_only=Truefor any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. checkpoint = torch.load(filename, lambda storage, loc: storage)
The text was updated successfully, but these errors were encountered: