isiahw1/c4a3049c-69cd5c22

RESI Real Estate Price Prediction Model

ONNX model for US residential real estate price prediction on Bittensor Subnet 46.

Model Details

• Input: 79 float32 features (property attributes, location, census data)
• Output: Predicted price in USD (float32)
• Format: ONNX (compatible with onnxruntime)
• Input name: m1_input
• Output name: m1_output
• License: MIT

Inference

import onnxruntime as ort
import numpy as np

sess = ort.InferenceSession("model.onnx", providers=["CPUExecutionProvider"])
features = np.zeros((1, 79), dtype=np.float32)  # 79 property features
result = sess.run(None, {"m1_input": features})[0]
predicted_price = result[0][0]  # USD

Feature Order

Features follow the RESI standard 79-feature schema as defined in feature_config.yaml.