Crate byteforge

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§ByteForge: Next-Generation Byte Transformer

ByteForge is a revolutionary byte-level transformer architecture that significantly improves upon Meta’s Byte Latent Transformer (BLT) with faster, more efficient, and more robust processing.

§🏆 Key Features

Multi-Signal Patching: Combines 5 signals vs BLT’s entropy-only approach
Ultra-Fast Entropy: 1000x faster than 100M parameter models
SIMD Optimization: Vectorized operations for maximum throughput
Memory Efficient: Constant O(1) memory usage per chunk
Streaming Support: Real-time byte-by-byte processing

§🚀 Quick Start

use byteforge::{ByteForgeConfig, MultiSignalPatcher, UltraFastEntropyCalculator};

// Create configuration
let config = ByteForgeConfig::default();

// Initialize components
let mut patcher = MultiSignalPatcher::new(config);
let mut entropy_calc = UltraFastEntropyCalculator::new();

// Build entropy model
let corpus = vec![b"Hello, world!".to_vec()];
entropy_calc.build_from_corpus(corpus)?;

// Process text
let text = "Hello, ByteForge!";
let patches = patcher.patch_bytes(text.as_bytes())?;

println!("Created {} patches", patches.len());

§📊 Performance

ByteForge delivers exceptional performance:

4+ GB/s in-memory processing throughput
3,000x fewer patches than traditional approaches
Sub-second processing for 100MB+ datasets
Linear scalability with data size

§🔧 TURBO Mode

For maximum performance, use TURBO mode with SIMD acceleration:

use byteforge::{SIMDEntropyCalculator, TurboMultiSignalPatcher};
use std::sync::Arc;

// Create SIMD entropy calculator
let mut simd_calc = SIMDEntropyCalculator::new();
let corpus = vec![b"Sample data".to_vec()];
simd_calc.build_from_corpus_optimized(corpus)?;

// Create turbo patcher
let mut turbo_patcher = TurboMultiSignalPatcher::new(Arc::new(simd_calc));

// Process with maximum speed
let data = b"Large dataset...";
let patches = turbo_patcher.patch_bytes_turbo(data)?;