The Well
is a 15TB dataset collection of physics simulations. This model is part of the models that have been benchmarked on the Well.
The models have been trained for a fixed time of 12 hours or up to 500 epochs, whichever happens first. The training was performed on a NVIDIA H100 96GB GPU.
In the time dimension, the context length was set to 4. The batch size was set to maximize the memory usage. We experiment with 5 different learning rates for each model on each dataset.
We use the model performing best on the validation set to report test set results.
The reported results are here to provide a simple baseline.
They should not be considered as state-of-the-art
. We hope that the community will build upon these results to develop better architectures for PDE surrogate modeling.
To load the UNetConvNext model trained on the
shear_flow
of the Well, use the following commands.
from the_well.benchmark.models import UNetConvNext
model = UNetConvNext.from_pretrained("polymathic-ai/UNetConvNext-shear_flow")
Runs of polymathic-ai UNetConvNext-shear_flow on huggingface.co
12
Total runs
0
24-hour runs
1
3-day runs
1
7-day runs
-6
30-day runs
More Information About UNetConvNext-shear_flow huggingface.co Model
UNetConvNext-shear_flow huggingface.co
UNetConvNext-shear_flow huggingface.co is an AI model on huggingface.co that provides UNetConvNext-shear_flow's model effect (), which can be used instantly with this polymathic-ai UNetConvNext-shear_flow model. huggingface.co supports a free trial of the UNetConvNext-shear_flow model, and also provides paid use of the UNetConvNext-shear_flow. Support call UNetConvNext-shear_flow model through api, including Node.js, Python, http.
UNetConvNext-shear_flow huggingface.co is an online trial and call api platform, which integrates UNetConvNext-shear_flow's modeling effects, including api services, and provides a free online trial of UNetConvNext-shear_flow, you can try UNetConvNext-shear_flow online for free by clicking the link below.
polymathic-ai UNetConvNext-shear_flow online free url in huggingface.co:
UNetConvNext-shear_flow is an open source model from GitHub that offers a free installation service, and any user can find UNetConvNext-shear_flow on GitHub to install. At the same time, huggingface.co provides the effect of UNetConvNext-shear_flow install, users can directly use UNetConvNext-shear_flow installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
UNetConvNext-shear_flow install url in huggingface.co: