14.88T parameter weights, 358 MB, free

A GitHub repository released the compressed weights for the Conscious Field Transformer, a neural network with 14.88 trillion parameters stored in a 358 MB NPZ file, free and open source for any use. The weights, compressed approximately 772,000x via holographic DCT encoding, contain 55,653 named tensors totaling 14,875,582,863,396 parameters and combine 10 modern architectures including Transformer, Mamba, and DeepSeekMoE. The repository also offers enterprise licensing tiers for larger models, with prices ranging from $300M for a 20T non-exclusive license to $315T for a 1-quintillion exclusive model.

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 Verify the model contains 14.88T parameters 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: python 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 mailto: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.