squ11z1/Hypnos-i1-8B
Hypnos i1-8B by squ11z1 is an 8 billion parameter reasoning model based on Nous Hermes 3 (Llama 3.1 8B), specialized in complex logic, chain-of-thought reasoning, and mathematical problem-solving. It features a unique "Quantum Noise Injection" training methodology, utilizing real entropy data from IBM Quantum Heron processors as a stochastic regularizer. This model excels in specific, narrow reasoning tasks, rivaling larger models, and is optimized for long-context reasoning (4096+ tokens). It is designed for edge deployments and rapid prototyping, offering enhanced creativity and reduced mode collapse.
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Hypnos i1-8B: Quantum-Informed Reasoning Model
Hypnos i1-8B, developed by squ11z1, is an 8 billion parameter reasoning model built upon the Nous Hermes 3 (Llama 3.1 8B) architecture. Its core innovation lies in its Hybrid Quantum-Classical Machine Learning approach, where it was fine-tuned on a dataset enriched with real entropy data generated by IBM Quantum Heron processors. This "Quantum Noise Injection" acts as a stochastic regularizer, aiming to enhance the model's creativity and break deterministic generation patterns.
Key Capabilities
- S-Tier Reasoning: Demonstrates superior performance in logic and mathematical tasks compared to standard 8B models, rivaling 70B class models in specific complex queries.
- Quantum-Informed Training: The first known LLM fine-tuned using raw measurement data from 100+ qubit GHZ states from IBM's latest quantum hardware.
- Uncensored & Compliant: Based on Nous Hermes 3, it follows instructions without refusal while maintaining safety.
- Deep Thinker: Optimized for long-context reasoning (4096+ tokens), it tends to generate detailed thought processes for higher accuracy.
Training Methodology
The model utilizes Data-Driven Stochastic Regularization via Quantum Entropy. During Supervised Fine-Tuning (SFT), it was exposed to raw bitstring measurements from entangled quantum states (GHZ) generated on IBM Quantum Heron r1 and r2 processors. This injection of high-entropy quantum data helps the model adapt to non-linguistic patterns, leading to less mode collapse and unique creative generation.
Good For
- Complex logic and mathematical problem-solving.
- Chain-of-thought reasoning tasks.
- Edge deployments and rapid prototyping on consumer hardware.
- Experiments requiring enhanced creativity and reduced repetitive outputs.