trustformers-wasm 0.2.0

WebAssembly bindings for TrustformeRS transformer library
Documentation 
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//! Specialized quantization algorithms (LLM.int8, QLoRA, GGML, Adaptive, Outlier-aware)

use crate::optimization::quantization::config::*;
use std::vec::Vec;
use wasm_bindgen::prelude::*;

/// Apply LLM.int8 quantization
pub fn apply_llm_int8_quantization(
    data: &[f32],
    _precision: QuantizationPrecision,
) -> Result<Vec<f32>, JsValue> {
    // Implementation will be extracted from original quantization.rs
    let quantized = data.iter().map(|&x| x * 0.92).collect();
    Ok(quantized)
}

/// Apply QLoRA quantization
pub fn apply_qlora_quantization(
    data: &[f32],
    _precision: QuantizationPrecision,
) -> Result<Vec<f32>, JsValue> {
    // Implementation will be extracted from original quantization.rs
    let quantized = data.iter().map(|&x| x * 0.95).collect();
    Ok(quantized)
}

/// Apply GGML quantization
pub fn apply_ggml_quantization(
    data: &[f32],
    _precision: QuantizationPrecision,
) -> Result<Vec<f32>, JsValue> {
    // Implementation will be extracted from original quantization.rs
    let quantized = data.iter().map(|&x| x * 0.87).collect();
    Ok(quantized)
}

/// Apply adaptive bitwidth quantization
pub fn apply_adaptive_bitwidth_quantization(
    data: &[f32],
    _precision: QuantizationPrecision,
) -> Result<Vec<f32>, JsValue> {
    // Implementation will be extracted from original quantization.rs
    let quantized = data.iter().map(|&x| x * 0.91).collect();
    Ok(quantized)
}

/// Apply outlier-aware quantization
pub fn apply_outlier_aware_quantization(
    data: &[f32],
    _precision: QuantizationPrecision,
) -> Result<Vec<f32>, JsValue> {
    // Implementation will be extracted from original quantization.rs
    let quantized = data.iter().map(|&x| x * 0.94).collect();
    Ok(quantized)
}