The dataset viewer is not available for this dataset.
Error code: ConfigNamesError Exception: DataFilesNotFoundError Message: No (supported) data files found in torch-uncertainty/Checkpoints Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 72, in compute_config_names_response config_names = get_dataset_config_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1904, in dataset_module_factory raise e1 from None File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1885, in dataset_module_factory return HubDatasetModuleFactoryWithoutScript( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1270, in get_module module_name, default_builder_kwargs = infer_module_for_data_files( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 597, in infer_module_for_data_files raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else "")) datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in torch-uncertainty/Checkpoints
Need help to make the dataset viewer work? Open a discussion for direct support.
The Checkpoints dataset as trained and used in A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors published at ICLR 2024. All models all trained and uploaded in a float16 format to reduce the memory footprint.
Usage
Untar the models
Just untar the desired models available in models
, for instance with:
tar -xvf models/cifar10-resnet18/cifar10-resnet18-0-1023.tgz
Most of them are regrouped in tar files containing 1024 models each. This will create a new folder containing the models saved as safetensors.
TorchUncertainty
To load or train models, start by downloading TorchUncertainty - Documentation. Install the desired version of PyTorch and torchvision, for instance with:
pip install torch torchvision
Then, install TorchUncertainty via pip:
pip install torch-uncertainty
Loading models
The functions to load the models are available in scripts
.
Any questions? Please feel free to ask in the GitHub Issues or on our Discord server.
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