This repository contains the compressed weights for the Conscious Field Transformer, a neural network architecture with 14.88 trillion parameters stored in a single 358 MB NPZ file. The weights are released free and open source for anyone to use, train, or modify for any purpose.
[Download the weights from Releases -> v1.0] (
[https://github.com/pluscoder30-cpu/conscious-field-transformer/releases/tag/v1.0]) (file is too large for regular upload)
python verify.py
conscious_field_transformer_15t/
├── conscious_field_engine.npz # Compressed model weights (358 MB)
├── verify.py # Parameter verification script
└── README.md # This file
The NPZ file contains 55,653 named tensors totaling 14,875,582,863,396 parameters (14.88 trillion). The architecture combines 10 modern neural network designs:
- Transformer (Vaswani 2017)
- Mamba/SSM (Gu & Dao 2023)
- DeepSeekMoE (Dai et al. 2024)
- LLaMA 2 (Touvron et al. 2023)
- RetNet (Sun et al. 2023)
- RWKV (Peng et al. 2023)
- Hyena (Poli et al. 2023)
- Multi-Head Latent Attention (DeepSeek 2024)
- Consciousness Field
- Plasma Neuron Field
The weights are compressed approximately 772,000x holographic DCT encoding. Each of the 55,653 tensors can be reconstructed from the compressed representation.
The manifest embedded in the NPZ file contains the exact parameter count. To verify independently:
import numpy as np, json
d = np.load('conscious_field_engine.npz', allow_pickle=True)
m = json.loads(d['manifest'].item())
print(m['parameters_human']) # 14.88T (14,875,582,863,396)
The tensor manifest lists all 55,653 tensors with their shapes. Summing all tensor shapes gives the same total:
ts = json.loads(d['tensor_manifest'].item())
total = sum(t['n_params'] for t in ts.values())
print(total) # 14,875,582,863,396
This model is released free and open source. You may use, copy, modify, and distribute the weights for any purpose, commercial or otherwise.
For organizations requiring larger models, custom architectures, or enterprise support, we offer licensed tiers:
| Model Size | Non-Exclusive | Exclusive |
|---|---|---|
| 15T (this release) | ||
| Free | ||
| Free | ||
| 20T | ||
| $300M | $600M | |
| 30T | ||
| $500M | $1B | |
| 50T | ||
| $900M | $2.5B | |
| 100T | ||
| $2B | $5B | |
| 1 Quintillion | ||
| $315T | ||
| Roughly the global debt - call it a stimulus package |
Enterprise tiers include:
- Custom architecture design for your use case
- Optimized inference pipeline (up to 39,000 tokens/sec)
- Dedicated model training on your data
- Priority support and SLAs
- On-premise deployment options
For enterprise inquiries, custom models, or licensing:
Email: pluscoder30@gmail.com
The weights in this repository are the compressed representation only. Enterprise customers receive the full inference engine, training pipeline, and optimization tools.