Expand description
Quantum Large Language Models (QLLMs)
This module implements quantum-enhanced large language models that leverage quantum computing principles for improved language understanding, generation, and reasoning capabilities. It builds on quantum transformers with advanced features like quantum memory, quantum reasoning, and quantum-classical hybrid processing.
Structs§
- Generation
Config - Text generation parameters
- Generation
Statistics - Generation statistics
- QLLM
Training Config - Training configuration for QLLMs
- Quality
Metrics - Quality metrics for generated text
- Quantum
Analogy Engine - Quantum analogy engine
- Quantum
Associative Memory - Quantum associative memory
- Quantum
Episode - Quantum episodic memory
- QuantumLLM
- Main Quantum Large Language Model
- QuantumLLM
Config - Quantum Large Language Model configuration
- Quantum
Memory Config - Quantum memory configuration
- Quantum
Memory System - Quantum memory system
- Quantum
Reasoning Config - Quantum reasoning configuration
- Quantum
Reasoning Module - Quantum reasoning module
- Subword
Tokenizer - Subword tokenizer
- Vocabulary
- Vocabulary management
Enums§
- Memory
Retrieval Type - Memory retrieval mechanisms
- Model
Scale - Model scale variants
- Quantum
Parameter Update - Quantum parameter update strategies