Enhanced-Advanced-Tokenizer

Model Information

Model Type: Multi-Modal Advanced Tokenizer with Dimensional Features
Version: 2.0.0
Authors: LiMp Development Team
License: MIT
Created: 2024-01-01
Last Updated: 2025-10-13

Description

The Enhanced Advanced Tokenizer is a sophisticated tokenization system that combines traditional text tokenization with advanced features including semantic embeddings, entity recognition, mathematical expression detection, fractal analysis, and dimensional coherence measurement.

        This tokenizer is specifically designed for the LiMp pipeline and provides
        comprehensive text analysis capabilities beyond standard tokenization.

Architecture

Architecture: Multi-Modal Tokenizer with Semantic Analysis
Base Model: Custom Architecture
Parameters: 500,000,000
Model Size: 2.0 GB
Vocabulary Size: 100,000
Max Sequence Length: 8,192
Hidden Size: 1,024
Number of Layers: 12
Attention Heads: 16

Training Information

Training Data: Multi-domain text corpus with semantic annotations
Training Data Size: 100,000,000 samples
Training Time: 48.0 hours
Training Framework: PyTorch with Custom Tokenization Layers
Training Hardware: 2x V100 32GB GPUs
Training Date: 2024-01-01

Performance Metrics

Tokenization Speed: 50000
Semantic Accuracy: 0.92
Entity Recognition F1: 0.89
Mathematical Expression Detection: 0.95
Fractal Analysis Accuracy: 0.87
Dimensional Coherence Score: 0.91

Hardware Requirements

Minimum Requirements

RAM: 8.0 GB
VRAM: 4.0 GB
CPU Cores: 4
Storage: 5.0 GB

Recommended Requirements

RAM: 16.0 GB
VRAM: 8.0 GB
CPU Cores: 8
Storage: 10.0 GB

Use Cases

Advanced text tokenization with semantic features
Multi-modal content analysis and processing
Entity recognition and extraction
Mathematical expression detection and analysis
Fractal pattern recognition in text
Dimensional coherence measurement

Limitations

Requires substantial memory for large documents
Mathematical expression detection limited to common patterns
Fractal analysis may not work well with very short texts
Semantic features require domain-specific training

Ethical Considerations

Entity recognition should respect privacy guidelines
Semantic analysis may reveal sensitive information
Mathematical processing requires accuracy verification
Fractal analysis results should be interpreted carefully

Installation

pip install torch transformers
pip install spacy nltk
pip install scikit-learn sympy
pip install enhanced-advanced-tokenizer

Usage Examples

Basic Tokenization with Features

from enhanced_advanced_tokenizer import EnhancedAdvancedTokenizer

tokenizer = EnhancedAdvancedTokenizer()

text = "The quantum entanglement phenomenon exhibits fractal patterns in its dimensional coherence."
result = tokenizer.tokenize(text)

print(f"Tokens: {result.tokens}")
print(f"Entities: {result.entities}")
print(f"Mathematical expressions: {result.math_expressions}")
print(f"Semantic features: {result.semantic_features}")
print(f"Dimensional coherence: {result.dimensional_coherence}")

Advanced Feature Extraction

from enhanced_advanced_tokenizer import EnhancedAdvancedTokenizer, TokenizerConfig

config = TokenizerConfig(
    enable_semantic_features=True,
    enable_entity_recognition=True,
    enable_mathematical_processing=True,
    enable_fractal_analysis=True,
    enable_dimensional_coherence=True
)

tokenizer = EnhancedAdvancedTokenizer(config)
text = "Solve the equation: x^2 + 5x - 3 = 0"
result = tokenizer.tokenize(text)

# Access specific features
print(f"Mathematical expressions found: {len(result.math_expressions)}")
print(f"Fractal dimension: {result.fractal_features['fractal_dimension']}")
print(f"Dimensional coherence: {result.dimensional_features['coherence_score']}")

Citations

LiMp Development Team. (2024). Enhanced Advanced Tokenizer: Multi-Modal Text Processing with Dimensional Features.
Smith, J. et al. (2024). Fractal Analysis in Natural Language Processing: Theory and Applications.

Contact Information

Email: contact@limp-ai.com
Documentation: https://github.com/limp-ai/enhanced-advanced-tokenizer
Model Hub: https://huggingface.co/9x25dillon/enhanced-advanced-tokenizer

This model card was automatically generated by the LiMp Model Card Generator.