polymath
Datasets
All datasets matching “polymath”shear_flow
How To Load from HuggingFace Hub
Be sure to have the_well installed (pip install the_well)
Use the WellDataModule to retrieve data as follows:
from the_well.data import WellDataModule
# The following line may take a couple of minutes to instantiate the datamodule
datamodule = WellDataModule(
"hf://datasets/polymathic-ai/",
"shear_flow",
)
train_dataloader = datamodule.train_dataloader()
for batch in dataloader:
# Process training batch
...
Periodic… See the full description on the dataset page: https://huggingface.co/datasets/polymathic-ai/shear_flow.PolyMath
PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts
PolyMath is a multilingual mathematical reasoning benchmark covering 18 languages and 4 easy-to-hard difficulty levels. Our benchmark ensures difficulty comprehensiveness, language diversity, and high-quality translation, making it a highly discriminative multilingual mathematical benchmark in the era of reasoning LLMs.
📈 Broad Difficulty Range: PolyMath defines and partitions… See the full description on the dataset page: https://huggingface.co/datasets/Qwen/PolyMath.rayleigh_benardThis Dataset is part of The Well Collection.
How To Load from HuggingFace Hub
Be sure to have the_well installed (pip install the_well)
Use the WellDataModule to retrieve data as follows:
from the_well.benchmark.data import WellDataModule
# The following line may take a couple of minutes to instantiate the datamodule
datamodule = WellDataModule(
"hf://datasets/polymathic-ai/",
"rayleigh_benard",
)
train_dataloader = datamodule.train_dataloader()
for batch in dataloader:… See the full description on the dataset page: https://huggingface.co/datasets/polymathic-ai/rayleigh_benard.active_matter
How To Load from HuggingFace Hub
Be sure to have the_well installed (pip install the_well)
Use the WellDataModule to retrieve data as follows:
from the_well.benchmark.data import WellDataModule
# The following line may take a couple of minutes to instantiate the datamodule
datamodule = WellDataModule(
"hf://datasets/polymathic-ai/",
"active_matter_cloud_optimized",
)
train_dataloader = datamodule.train_dataloader()
for batch in dataloader:
# Process training batch… See the full description on the dataset page: https://huggingface.co/datasets/polymathic-ai/active_matter.MHD_64
Magnetohydrodynamics (MHD) compressible turbulence
NOTE: This dataset is available in two different resolutions $256^3$ for MHD_256 and $64^3$ for MHD_64. The data was first generated at $256^3$ and then downsampled to $64^3$ after anti-aliasing with an ideal low-pass filter. The data is available in both resolutions.
One line description of the data: This is an MHD fluid flows in the compressible limit (subsonic, supersonic, sub-Alfvenic, super-Alfvenic).
Longer description of the… See the full description on the dataset page: https://huggingface.co/datasets/polymathic-ai/MHD_64.turbulence_gravity_coolingThis Dataset is part of The Well Collection.
How To Load from HuggingFace Hub
Be sure to have the_well installed (pip install the_well)
Use the WellDataModule to retrieve data as follows:
from the_well.data import WellDataModule
# The following line may take a couple of minutes to instantiate the datamodule
datamodule = WellDataModule(
"hf://datasets/polymathic-ai/",
"turbulence_gravity_cooling",
)
train_dataloader = datamodule.train_dataloader()
for batch in dataloader:… See the full description on the dataset page: https://huggingface.co/datasets/polymathic-ai/turbulence_gravity_cooling.