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CHECKLIST.txt

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+RESI miner bundle — USD ONNX + subnet feature_config (14-feature schema)
+================================================================================
+
+A) Training (must match validator: ONNX outputs USD, MAPE vs dollar price)
+
+  1. Default train_real_estate.py exports a **single fused ONNX**: raw features
+     (same order as feature_config) → StandardScaler inside the graph → trees →
+     optional expm1 → USD tensor ``price_usd``. You do **not** need --no-log-target
+     for a valid miner model if you keep default fusion (log1p training + expm1
+     fused). Input name is ``float_input`` for fused exports.
+
+     Alternative — train directly in dollars (no log head in ONNX):
+
+       MPLBACKEND=Agg python train_real_estate.py \\
+         --data training_data.json \\
+         --catboost \\
+         --out artifacts_miner_usd \\
+         --no-log-target
+
+     Legacy unfused tree-only ONNX (no scaler / no expm1 in graph):
+
+       ... --no-onnx-fusion
+
+     Use --all / --xgboost / --lightgbm instead of --catboost if you prefer.
+
+  2. Keep the same feature columns as this bundle: train with DEFAULT redundant
+     dropping (omit --no-drop-redundant) so you have exactly the 14 features
+     listed in miner_submission/feature_config.json.
+
+     If you train with --no-drop-redundant (17 columns), regenerate the JSON:
+
+       MPLBACKEND=Agg python train_real_estate.py ... --no-drop-redundant \\
+         --write-miner-feature-config miner_submission/feature_config.json
+
+B) Export files for chain / HF repo
+
+  3. Copy the chosen ONNX to your repo as model.onnx (e.g. from
+     artifacts_miner_usd/catboost_price_model.onnx).
+
+  4. Commit miner_submission/feature_config.json alongside the model (same
+     feature order as training / encoder).
+
+  5. ONNX input: one float tensor, shape [N, 14], columns in the exact order
+     of "features" in feature_config.json. Fused models use input ``float_input``.
+     Output is typically a single tensor; fused USD models name it ``price_usd``
+     (take index 0 if your runner binds by position).
+
+C) Validate JSON against subnet rules (optional)
+
+  cd /home/RESI-models
+  .venv/bin/python -c "
+  from pathlib import Path
+  from real_estate.data.config_encoder import load_feature_config
+  load_feature_config(Path('/home/46/miner_submission/feature_config.json'))
+  print('feature_config.json OK')
+  "
+
+D) Do not rely on target_transform.json on-chain — the validator does not apply
+   expm1; the model must emit dollars.
+
+E) You cannot change the eval system — submission-only rules
+
+   The validator always: encodes raw API fields → float32 matrix (same order as
+   your feature_config) → ONNX → treats outputs as USD for MAPE.
+
+   Therefore you MUST NOT depend on any extra JSON, hooks, or server-side
+   preprocessing. Everything the model needs must be inside model.onnx OR you
+   must train without that preprocessing:
+
+   • Feature normalization (z-score, min-max): only valid if you fuse those ops
+     into the ONNX graph ahead of the trees. Default train_real_estate.py does
+     this (StandardScaler → trees → optional expm1). Training with a sklearn
+     scaler but submitting plain tree ONNX on raw inputs = wrong.
+
+   • log1p(price) training: only valid if the ONNX output is already USD, i.e.
+     expm1 is in the graph (default fused export) or you use --no-log-target.
+
+   • For gradient-boosted trees on tabular data, raw features + USD target is
+     usually enough; focus on data and regularization rather than z-score unless
+     you invest in ONNX fusion tools.
+
+   Minimum viable submission: model.onnx (raw in → USD out) + feature_config.json
+   matching column order; no other files required by default.

LICENSE

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+# Business Source License 1.1
+
+**Licensor:** RESI  
+**Licensed Work:** Subnet 46 Validator Software, Incentive Mechanism, Agent Codebase, and associated Model Weights distributed by RESI (the "Licensed Work").  
+**Additional Use Grant:** You may use the Licensed Work in production solely for operating a Miner or Validator node within Bittensor Network's Subnet 46, in accordance with the Bittensor protocol rules.  
+**Change Date:** January 1, 2030  
+**Change License:** Apache License 2.0  
+
+---
+
+## Notice
+
+Copyright © 2026 RESI. All rights reserved.
+
+---
+
+## Terms and Conditions
+
+### 1. Grant of Rights
+
+Subject to the terms and conditions of this License, Licensor hereby grants you a worldwide, royalty-free, non-exclusive license to:
+
+a) Copy, modify, and create derivative works of the Licensed Work;  
+b) Redistribute the Licensed Work and derivative works; and  
+c) Make non-production use of the Licensed Work.
+
+Licensor also grants you the Additional Use Grant specified above.
+
+### 2. Restrictions
+
+You may **NOT** use the Licensed Work for any of the following purposes without obtaining a separate commercial license from RESI:
+
+a) **Competitive Products:** Operating a commercial product or service that competes with RESI or Subnet 46, including but not limited to:
+   - Software-as-a-Service (SaaS) offerings
+   - API services or hosted platforms
+   - Commercial AI model evaluation or scoring services
+   - Any service that uses the Licensed Work's methodology outside the Bittensor Network
+
+b) **Commercial Distribution:** Selling, licensing, or distributing the Licensed Work or derivative works as a commercial product outside the Bittensor Network;
+
+c) **Model Training:** Using the Licensed Work to train, fine-tune, or improve AI models for commercial purposes outside of Subnet 46 mining or validation activities;
+
+d) **Unauthorized Production Use:** Any production use outside of the expressly permitted Bittensor Subnet 46 participation.
+
+### 3. Permitted Uses
+
+The following uses are **permitted** without obtaining a commercial license:
+
+a) Operating Miner or Validator nodes on Bittensor Subnet 46;  
+b) Non-production research, testing, development, and evaluation;  
+c) Educational and academic purposes;  
+d) Contributing improvements back to RESI (subject to the Contributor Agreement);  
+e) Internal business evaluation (non-production environments only).
+
+### 4. Change License
+
+On the Change Date specified above (January 1, 2030), this Business Source License will automatically terminate, and the Licensed Work will become available under the terms of the Change License (Apache License 2.0).
+
+### 5. Trademark Rights
+
+This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Licensed Work.
+
+### 6. Disclaimer of Warranty
+
+THE LICENSED WORK 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, TITLE, AND NONINFRINGEMENT. IN NO EVENT SHALL THE LICENSOR, CONTRIBUTORS, 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 LICENSED WORK OR THE USE OR OTHER DEALINGS IN THE LICENSED WORK.
+
+### 7. Limitation of Liability
+
+TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, IN NO EVENT SHALL THE LICENSOR BE LIABLE FOR ANY SPECIAL, INCIDENTAL, INDIRECT, OR CONSEQUENTIAL DAMAGES WHATSOEVER (INCLUDING, WITHOUT LIMITATION, DAMAGES FOR LOSS OF BUSINESS PROFITS, BUSINESS INTERRUPTION, LOSS OF BUSINESS INFORMATION, OR ANY OTHER PECUNIARY LOSS) ARISING OUT OF THE USE OF OR INABILITY TO USE THE LICENSED WORK, EVEN IF THE LICENSOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
+
+### 8. Termination
+
+This License and the rights granted hereunder will terminate automatically if you fail to comply with its terms. Upon termination, you must cease all use and distribution of the Licensed Work. Sections 6 (Disclaimer), 7 (Limitation of Liability), and 9 (General) shall survive any termination.
+
+### 9. General
+
+a) **Governing Law:** This License shall be governed by and construed in accordance with the laws of Wyoming, United States, excluding its conflicts of law provisions.
+
+b) **Severability:** If any provision of this License is held to be unenforceable, such provision shall be reformed only to the extent necessary to make it enforceable.
+
+c) **Entire Agreement:** This License constitutes the entire agreement between the parties with respect to the Licensed Work.
+
+d) **Modifications:** Licensor reserves the right to release the Licensed Work under different license terms or to stop distributing the Licensed Work at any time; provided, however that any such election will not serve to withdraw this License (or any other license that has been granted under the terms of this License), and this License will continue in full force and effect unless terminated as stated above.
+
+---
+
+## Commercial Licensing
+
+For commercial use outside the scope of the Additional Use Grant, please contact:
+
+**Email:** legal@resilabs.ai  
+**Website:** www.resilabs.ai
+
+---
+
+## Contributing
+
+If you wish to contribute to this project or submit models to Subnet 46, please review:
+
+- **Contributor Agreement:** [CONTRIBUTOR_AGREEMENT.md](./CONTRIBUTOR_AGREEMENT.md)
+- **Terms of Service:** [TERMS_OF_SERVICE.md](./TERMS_OF_SERVICE.md)
+
+---
+
+## Questions?
+
+For questions about this license, please contact legal@resilabs.ai
+
+---
+
+**Note:** This license is based on the Business Source License 1.1. For more information about BSL, visit: https://mariadb.com/bsl11/

README.md

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+---
+license: other
+license_name: resi-exclusive
+license_link: https://huggingface.co/resi-ai/model-license/blob/main/LICENSE
+tags:
+  - real-estate
+  - onnx
+  - bittensor
+  - resi
+---
+# RESI Real Estate Price Prediction Model
+
+ONNX model for US residential real estate price prediction.
+
+## Model Details
+- **Input**: 12 float32 features (property attributes, location, census data)
+- **Output**: Predicted price in USD
+- **Format**: ONNX (compatible with onnxruntime 1.20.1)
+- **License**: MIT

feature_config.json

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+{
+  "version": "1.0",
+  "features": [
+    "living_area_sqft",
+    "lot_size_sqft",
+    "bedrooms",
+    "bathrooms",
+    "latitude",
+    "longitude",
+    "home_type_SINGLE_FAMILY",
+    "home_type_MULTI_FAMILY",
+    "home_type_MANUFACTURED",
+    "home_type_LOT",
+    "home_type_HOME_TYPE_UNKNOWN",
+    "home_type_nan",
+    "year_built",
+    "stories"
+  ]
+}

price_model.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7e4aaf8f620abe3c36acdee39a70b9bee472449effd0071d9fa211a385efe787
+size 1837709