runtime error

Exit code: 1. Reason: vec2-base and are newly initialized: ['classifier.bias', 'classifier.weight', 'projector.bias', 'projector.weight'] You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference. /usr/local/lib/python3.10/site-packages/transformers/configuration_utils.py:306: UserWarning: Passing `gradient_checkpointing` to a config initialization is deprecated and will be removed in v5 Transformers. Using `model.gradient_checkpointing_enable()` instead, or if you are using the `Trainer` API, pass `gradient_checkpointing=True` in your `TrainingArguments`. warnings.warn( /home/user/app/app.py:35: FutureWarning: You are using `torch.load` with `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_only` will 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=True` for 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('pytorch_model.bin', map_location=torch.device('cpu')) Traceback (most recent call last): File "/home/user/app/app.py", line 65, in <module> inputs=gr.Audio(source="microphone", type="filepath", optional=False, label="Speak to classify your voice!"), # record audio, save in temp file to feed to inference func File "/usr/local/lib/python3.10/site-packages/gradio/component_meta.py", line 179, in wrapper return fn(self, **kwargs) TypeError: Audio.__init__() got an unexpected keyword argument 'source'

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