Instructions to use taiger7196/MrMaie-V5-Coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taiger7196/MrMaie-V5-Coder with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("taiger7196/MrMaie-V5-Coder", dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- it
- en
license: other
library_name: transformers
tags:
- ternary-logic
- sub-1bit
- chronos-weave
- paradox-engine
model_name: MrMaie V5 Coder
♕ MrMaie V5 Coder: Chronos-Weave Edition
MrMaie V5 represents the pinnacle of sub-1bit coding models, utilizing the Chronos-Weave architecture for near-infinite context management.
Key Specifications
- Model Type: Ternary-Logic Coder (1.58-bit Weights)
- Context Window: 5,000,000 Tokens (Beacon-Compressed)
- VRAM Footprint: < 1.0 GB (Optimized for T4/L4 hardware)
- Reasoning Engine: Paradox-Engine v5 (Deductive Data Synthesis)
Chronos-Weave & Beacons
Unlike standard Transformers that suffer from KV-cache bloating, V5 uses Beacons. Every 8k tokens are compressed into a latent vector (Beacon) that anchors the next sequence. This allows the model to 'remember' entire codebases with only 0.0012 GB of metadata overhead.
Usage
To activate the heavy reasoning mode, use the following system prompt:
Sei MrMaie V5 Infernus. Risolvi il task con la massima efficienza hardware e densità logica.
License
Proprietary / Research Use Only