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 66, 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 1873, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1854, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1245, 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 595, 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/CheckpointsNeed 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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