Publish fixed-update physics study checkpoints and measured metadata

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Libor Burian
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -0,0 +1,44 @@
+---
+license: mit
+library_name: pytorch
+tags:
+- physics
+- simulation
+- attention-residuals
+- gphyt
+---
+# GPhyT-S: block
+
+Final fixed-update checkpoints from the paired GPhyT Attention Residuals study by Libor Burian.
+The architecture uses twelve layers, width 192, MLP width 768, three heads, four context frames,
+128x64 fields, and five canonical channels. Mode: `block`. Training updates: 3175.
+
+## Use and evaluation
+
+Clone the [study repository](https://github.com/BurnyCoder/general-physics-attention-residuals-transformer),
+install with `uv sync --locked`, and construct `make_model(config, residual_mode, seed)` from
+`gphyt_attnres_study.model`. Load `seedN/model.safetensors` with `safetensors.torch.load_file`.
+Normalize each active channel using this release's per-dataset `normalization.json`; absent
+channels remain zero and must be masked out of metrics and autoregressive feedback.
+The CLI evaluation phase and tests specify the exact inference and scoring procedure.
+
+Each `seedN/evaluation.json`, when available, reports measured one-step, 12-step, and 24-step
+errors. `runs.json` retains failed or omitted seeds. No unmeasured improvement is asserted here.
+These models were trained from scratch on the preregistered subset of
+[The Well](https://arxiv.org/abs/2412.00568), with official trajectory splits and train-only normalization.
+They are research surrogates, not numerical solvers or validated predictors for unseen physics.
+Coarse spatial resolution, a bounded local compute budget, and six primary seed pairs limit inference.
+Buoyancy is a separate channel and is not temperature.
+Training used BF16 autocast. Eligible FLA routing contractions inherit autocast despite explicit
+FP32 tensor casts; raw Block sums accumulate in the FP32 residual stream. The post-freeze
+precision-description disclosure and pre-evaluation intervention correction are documented in
+the [architecture audit](https://github.com/BurnyCoder/general-physics-attention-residuals-transformer/blob/main/reports/architecture-audit.md).
+All held-out trajectories share their first frame with training at another physical parameter setting.
+The official-split evaluation does not establish generalization to entirely unseen initial conditions;
+see the repository's `reports/data-preparation.md` and `reports/data_audit.json` for the exact overlap audit.
+
+## Sources and attribution
+
+- [GPhyT paper](https://arxiv.org/abs/2509.13805) and [official MIT code](https://github.com/FloWsnr/General-Physics-Transformer).
+- [Attention Residuals](https://arxiv.org/abs/2603.15031) and [FLA MIT operator](https://github.com/fla-org/flash-linear-attention).
+- Exact pinned revisions, licenses, reports, and the paper are in the study repository.

config.json

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+}

frozen_protocol.json

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runs.json

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