Push model using huggingface_hub.

README.md

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+---
+datasets: polymathic-ai/acoustic_scattering_maze
+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.
+
+# Tensorized Fourier Neural Operator
+
+Implementation of the [Tensorized Fourier Neural Operator](https://arxiv.org/abs/2310.00120) 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 TFNO on different datasets of the Well.
+
+| Dataset | Learning Rate | Epoch | VRMSE |
+|---------|----------------|-------|-------|
+| [acoustic_scattering_maze](https://huggingface.co/polymathic-ai/TFNO-acoustic_scattering) | 1E-3 | 27 | 0.5034 |
+| [active_matter](https://huggingface.co/polymathic-ai/TFNO-active_matter) | 1E-3 | 243 | 0.3342 |
+| [convective_envelope_rsg](https://huggingface.co/polymathic-ai/TFNO-convective_envelope_rsg) | 1E-3 | 13 | 0.0195 |
+| [gray_scott_reaction_diffusion](https://huggingface.co/polymathic-ai/TFNO-gray_scott_reaction_diffusion) | 5E-3 | 45 | 0.1784 |
+| [helmholtz_staircase](https://huggingface.co/polymathic-ai/TFNO-helmholtz_staircase) | 5E-4 | 131 | 0.00031 |
+| [MHD_64](https://huggingface.co/polymathic-ai/TFNO-MHD_64) | 1E-3 | 155 | 0.3347 |
+| [planetswe](https://huggingface.co/polymathic-ai/TFNO-planetswe) | 5E-4 | 49 | 0.1061 |
+| [post_neutron_star_merger](https://huggingface.co/polymathic-ai/TFNO-post_neutron_star_merger) | 5E-4 | 99 | 0.4064 |
+| [rayleigh_benard](https://huggingface.co/polymathic-ai/TFNO-rayleigh_benard) | 1E-4 | 31 | 0.8568 |
+| [rayleigh_taylor_instability](https://huggingface.co/polymathic-ai/TFNO-rayleigh_taylor_instability) | 1E-4 | 175 | 0.2251 |
+| [shear_flow](https://huggingface.co/polymathic-ai/TFNO-shear_flow) | 1E-3 | 24 | 0.3626 |
+| [supernova_explosion_64](https://huggingface.co/polymathic-ai/TFNO-supernova_explosion_64) | 1E-4 | 35 | 0.3645 |
+| [turbulence_gravity_cooling](https://huggingface.co/polymathic-ai/TFNO-turbulence_gravity_cooling) | 5E-4 | 10 | 0.2789 |
+| [turbulent_radiative_layer_2D](https://huggingface.co/polymathic-ai/TFNO-turbulent_radiative_layer_2D) | 1E-3 | 500 | 0.4938 |
+| [viscoelastic_instability](https://huggingface.co/polymathic-ai/TFNO-viscoelastic_instability) | 5E-3 | 199 | 0.7021 |
+
+
+## Loading the model from Hugging Face
+
+To load the TFNO model trained on the `acoustic_scattering_maze` of the Well, use the following commands.
+
+```python
+from the_well.benchmark.models import TFNO
+
+model = TFNO.from_pretrained("polymathic-ai/TFNO-acoustic_scattering_maze")
+```

config.json

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+{
+  "dim_in": 14,
+  "dim_out": 3,
+  "gradient_checkpointing": false,
+  "hidden_channels": 128,
+  "modes1": 16,
+  "modes2": 16,
+  "modes3": 16,
+  "n_spatial_dims": 2,
+  "spatial_resolution": [
+    256,
+    256
+  ]
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:48d187aaa1ba08707dc17fee65e24dd9690ebae26fe4a2c9d23b8b12399d7af5
+size 77106860