Push model using huggingface_hub.

README.md

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+---
+datasets: polymathic-ai/helmholtz_staircase
+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.
+
+# CNextU-Net
+
+Implementation of the [U-Net model](https://arxiv.org/abs/1505.04597) using [ConvNext blocks](https://arxiv.org/abs/2201.03545).
+
+## Model Details
+
+For benchmarking on the Well, we used the following parameters.
+
+| Parameters          | Values |
+|---------------------|--------|
+| Spatial Filter Size | 7      |
+| Initial Dimension   | 42     |
+| Block per Stage     | 2      |
+| Up/Down Blocks      | 4      |
+| Bottleneck Blocks   | 1      |
+
+
+## Trained Model Versions
+
+Below is the list of checkpoints available for the training of CNextU-Net on different datasets of the Well.
+
+| Dataset | Learning Rate | Epoch | VRMSE |
+|---------|---------------|-------|-------|
+| [acoustic_scattering_maze](https://huggingface.co/polymathic-ai/UNetConvNext-acoustic_scattering) | 1E-3 | 10 | 0.0196 |
+| [active_matter](https://huggingface.co/polymathic-ai/UNetConvNext-active_matter) | 5E-3 | 156 | 0.0953 |
+| [convective_envelope_rsg](https://huggingface.co/polymathic-ai/UNetConvNext-convective_envelope_rsg) | 1E-4 | 5 | 0.0663 |
+| [gray_scott_reaction_diffusion](https://huggingface.co/polymathic-ai/UNetConvNext-gray_scott_reaction_diffusion) | 1E-4 | 15 | 0.3596 |
+| [helmholtz_staircase](https://huggingface.co/polymathic-ai/UNetConvNext-helmholtz_staircase) | 5E-4 | 47 | 0.00146 |
+| [MHD_64](https://huggingface.co/polymathic-ai/UNetConvNext-MHD_64) | 5E-3 | 59 | 0.1487 |
+| [planetswe](https://huggingface.co/polymathic-ai/UNetConvNext-planetswe) | 1E-2 | 18 | 0.3268 |
+| [post_neutron_star_merger](https://huggingface.co/polymathic-ai/UNetConvNext-post_neutron_star_merger) | - | - | - |
+| [rayleigh_benard](https://huggingface.co/polymathic-ai/UNetConvNext-rayleigh_benard) | 5E-4 | 12 | 0.4807 |
+| [rayleigh_taylor_instability](https://huggingface.co/polymathic-ai/UNetConvNext-rayleigh_taylor_instability) | 5E-3 | 56 | 0.3771 |
+| [shear_flow](https://huggingface.co/polymathic-ai/UNetConvNext-shear_flow) | 5E-4 | 9 | 0.3972 |
+| [supernova_explosion_64](https://huggingface.co/polymathic-ai/UNetConvNext-supernova_explosion_64) | 5E-4 | 13 | 0.2801 |
+| [turbulence_gravity_cooling](https://huggingface.co/polymathic-ai/UNetConvNext-turbulence_gravity_cooling) | 1E-3 | 3 | 0.2093 |
+| [turbulent_radiative_layer_2D](https://huggingface.co/polymathic-ai/UNetConvNext-turbulent_radiative_layer_2D) | 5E-3 | 495 | 0.1247 |
+| [viscoelastic_instability](https://huggingface.co/polymathic-ai/UNetConvNext-viscoelastic_instability) | 5E-4 | 114 | 0.1966 |
+
+
+## Loading the model from Hugging Face
+
+To load the UNetConvNext model trained on the `helmholtz_staircase` of the Well, use the following commands.
+
+```python
+from the_well.benchmark.models import UNetConvNext
+
+model = UNetConvNext.from_pretrained("polymathic-ai/UNetConvNext-helmholtz_staircase")
+```

config.json

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+{
+  "blocks_at_neck": 1,
+  "blocks_per_stage": 2,
+  "dim_in": 9,
+  "dim_out": 2,
+  "gradient_checkpointing": false,
+  "init_features": 42,
+  "n_spatial_dims": 2,
+  "spatial_resolution": [
+    1024,
+    256
+  ],
+  "stages": 4
+}

model.safetensors

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+oid sha256:dd702f0b8f56905e34af27af0a653e5e61d13fcd4357859faf7d5a2bf362b812
+size 74307152