Push model using huggingface_hub.

README.md

@@ -0,0 +1,64 @@
+---
+datasets: polymathic-ai/viscoelastic_instability
+tags:
+- physics
+---
+
+# Benchmarking Models on the Well
+
+[The Well](https://github.com/PolymathicAI/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.
+
+# Fourier Neural Operator
+
+Implementation of the [Fourier Neural Operator](https://arxiv.org/abs/2010.08895) provided by [`neuraloperator v0.3.0`](https://neuraloperator.github.io/dev/index.html).
+
+## Model Details
+
+For benchmarking on the Well, we used the following parameters.
+
+| Parameters  | Values |
+|-------------|--------|
+| Modes       | 16     |
+| Blocks      | 4      |
+| Hidden Size | 128    |
+
+
+## Trained Model Versions
+
+Below is the list of checkpoints available for the training of FNO on different datasets of the Well.
+
+| Dataset                                | Best Learning Rate | Epochs | VRMSE  |
+|----------------------------------------|--------------------|--------|--------|
+| [acoustic_scattering_maze](https://huggingface.co/polymathic-ai/FNO-acoustic_scattering_maze)             | 1E-3               | 27     | 0.5033 |
+| [active_matter](https://huggingface.co/polymathic-ai/FNO-active_matter)                                   | 5E-3               | 239    | 0.3157 |
+| [convective_envelope_rsg](https://huggingface.co/polymathic-ai/FNO-convective_envelope_rsg)               | 1E-4               | 14     | 0.0224 |
+| [gray_scott_reaction_diffusion](https://huggingface.co/polymathic-ai/FNO-gray_scott_reaction_diffusion)   | 1E-3               | 46     | 0.2044 |
+| [helmholtz_staircase](https://huggingface.co/polymathic-ai/FNO-helmholtz_staircase)                       | 5E-4               | 132    | 0.00160|
+| [MHD_64](https://huggingface.co/polymathic-ai/FNO-MHD_64)                                                 | 5E-3               | 170    | 0.3352 |
+| [planetswe](https://huggingface.co/polymathic-ai/FNO-planetswe)                                           | 5E-4               | 49     | 0.0855 |
+| [post_neutron_star_merger](https://huggingface.co/polymathic-ai/FNO-post_neutron_star_merger)             | 5E-4               | 104    | 0.4144 |
+| [rayleigh_benard](https://huggingface.co/polymathic-ai/FNO-rayleigh_benard)                               | 1E-4               | 32     | 0.6049 |
+| [rayleigh_taylor_instability](https://huggingface.co/polymathic-ai/FNO-rayleigh_taylor_instability)       | 5E-3               | 177    | 0.4013 |
+| [shear_flow](https://huggingface.co/polymathic-ai/FNO-shear_flow)                                         | 1E-3               | 24     | 0.4450 |
+| [supernova_explosion_64](https://huggingface.co/polymathic-ai/FNO-supernova_explosion_64)                 | 1E-4               | 40     | 0.3804 |
+| [turbulence_gravity_cooling](https://huggingface.co/polymathic-ai/FNO-turbulence_gravity_cooling)         | 1E-4               | 13     | 0.2381 |
+| [turbulent_radiative_layer_2D](https://huggingface.co/polymathic-ai/FNO-turbulent_radiative_layer_2D)     | 5E-3               | 500    | 0.4906 |
+| [viscoelastic_instability](https://huggingface.co/polymathic-ai/FNO-viscoelastic_instability)             | 5E-3               | 205    | 0.7195 |
+
+
+## Loading the model from Hugging Face
+
+To load the FNO model trained on the `viscoelastic_instability` of the Well, use the following commands.
+
+```python
+from the_well.benchmark.models import FNO
+
+model = FNO.from_pretrained("polymathic-ai/FNO-viscoelastic_instability")
+```

config.json

@@ -0,0 +1,14 @@
+{
+  "dim_in": 32,
+  "dim_out": 8,
+  "gradient_checkpointing": false,
+  "hidden_channels": 128,
+  "modes1": 16,
+  "modes2": 16,
+  "modes3": 16,
+  "n_spatial_dims": 2,
+  "spatial_resolution": [
+    512,
+    512
+  ]
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3c3b68712579a86e576b41b1d052cd7cd21c32dfe243fabd469cef25de9a6089
+size 76069152