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diff --git a/crates/ruvector-attention-node/npm/win32-x64-msvc/attention.win32-x64-msvc.node b/crates/ruvector-attention-node/npm/win32-x64-msvc/attention.win32-x64-msvc.node
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diff --git a/crates/ruvector-attention-wasm/pkg/LICENSE b/crates/ruvector-attention-wasm/pkg/LICENSE
new file mode 100644
index 00000000..2dd524ac
--- /dev/null
+++ b/crates/ruvector-attention-wasm/pkg/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 rUv
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/crates/ruvector-attention-wasm/pkg/README.md b/crates/ruvector-attention-wasm/pkg/README.md
new file mode 100644
index 00000000..7e11e537
--- /dev/null
+++ b/crates/ruvector-attention-wasm/pkg/README.md
@@ -0,0 +1,220 @@
+# ruvector-attention-wasm
+
+WebAssembly bindings for the ruvector-attention package, providing high-performance attention mechanisms for browser and Node.js environments.
+
+## Features
+
+- **Multiple Attention Mechanisms**:
+  - Scaled Dot-Product Attention
+  - Multi-Head Attention
+  - Hyperbolic Attention (for hierarchical data)
+  - Linear Attention (Performer-style)
+  - Flash Attention (memory-efficient)
+  - Local-Global Attention
+  - Mixture of Experts (MoE) Attention
+  - **CGT Sheaf Attention** (coherence-gated via Prime-Radiant)
+
+- **Training Utilities**:
+  - InfoNCE contrastive loss
+  - Adam optimizer
+  - AdamW optimizer (with decoupled weight decay)
+  - Learning rate scheduler (warmup + cosine decay)
+
+- **TypeScript Support**: Full type definitions and modern API
+
+## Installation
+
+```bash
+npm install ruvector-attention-wasm
+```
+
+## Usage
+
+### TypeScript/JavaScript
+
+```typescript
+import { initialize, MultiHeadAttention, utils } from 'ruvector-attention-wasm';
+
+// Initialize WASM module
+await initialize();
+
+// Create multi-head attention
+const attention = new MultiHeadAttention({ dim: 64, numHeads: 8 });
+
+// Prepare inputs
+const query = new Float32Array(64);
+const keys = [new Float32Array(64), new Float32Array(64)];
+const values = [new Float32Array(64), new Float32Array(64)];
+
+// Compute attention
+const output = attention.compute(query, keys, values);
+
+// Use utilities
+const similarity = utils.cosineSimilarity(query, keys[0]);
+```
+
+### Advanced Examples
+
+#### Hyperbolic Attention
+
+```typescript
+import { HyperbolicAttention } from 'ruvector-attention-wasm';
+
+const hyperbolic = new HyperbolicAttention({
+  dim: 128,
+  curvature: 1.0
+});
+
+const output = hyperbolic.compute(query, keys, values);
+```
+
+#### MoE Attention with Expert Stats
+
+```typescript
+import { MoEAttention } from 'ruvector-attention-wasm';
+
+const moe = new MoEAttention({
+  dim: 64,
+  numExperts: 4,
+  topK: 2
+});
+
+const output = moe.compute(query, keys, values);
+
+// Get expert utilization
+const stats = moe.getExpertStats();
+console.log('Load balance:', stats.loadBalance);
+```
+
+#### Training with InfoNCE Loss
+
+```typescript
+import { InfoNCELoss, Adam } from 'ruvector-attention-wasm';
+
+const loss = new InfoNCELoss(0.07);
+const optimizer = new Adam(paramCount, {
+  learningRate: 0.001,
+  beta1: 0.9,
+  beta2: 0.999,
+});
+
+// Training loop
+const lossValue = loss.compute(anchor, positive, negatives);
+optimizer.step(params, gradients);
+```
+
+#### Learning Rate Scheduling
+
+```typescript
+import { LRScheduler, AdamW } from 'ruvector-attention-wasm';
+
+const scheduler = new LRScheduler({
+  initialLR: 0.001,
+  warmupSteps: 1000,
+  totalSteps: 10000,
+});
+
+const optimizer = new AdamW(paramCount, {
+  learningRate: scheduler.getLR(),
+  weightDecay: 0.01,
+});
+
+// Training loop
+for (let step = 0; step < 10000; step++) {
+  optimizer.learningRate = scheduler.getLR();
+  optimizer.step(params, gradients);
+  scheduler.step();
+}
+```
+
+## Building from Source
+
+### Prerequisites
+
+- Rust 1.70+
+- wasm-pack
+
+### Build Commands
+
+```bash
+# Build for web (ES modules)
+wasm-pack build --target web --out-dir pkg
+
+# Build for Node.js
+wasm-pack build --target nodejs --out-dir pkg-node
+
+# Build for bundlers (webpack, vite, etc.)
+wasm-pack build --target bundler --out-dir pkg-bundler
+
+# Run tests
+wasm-pack test --headless --firefox
+```
+
+## API Reference
+
+### Attention Mechanisms
+
+- `MultiHeadAttention` - Standard multi-head attention
+- `HyperbolicAttention` - Attention in hyperbolic space
+- `LinearAttention` - Linear complexity attention (Performer)
+- `FlashAttention` - Memory-efficient attention
+- `LocalGlobalAttention` - Combined local and global attention
+- `MoEAttention` - Mixture of Experts attention
+- `CGTSheafAttention` - Coherence-gated via Prime-Radiant energy
+- `scaledDotAttention()` - Functional API for basic attention
+
+### CGT Sheaf Attention (Prime-Radiant Integration)
+
+The CGT (Coherence-Gated Transformer) Sheaf Attention mechanism uses Prime-Radiant's sheaf Laplacian energy to gate attention based on mathematical consistency:
+
+```typescript
+import { CGTSheafAttention } from 'ruvector-attention-wasm';
+
+const cgtAttention = new CGTSheafAttention({
+  dim: 128,
+  numHeads: 8,
+  coherenceThreshold: 0.3,  // Block if energy > threshold
+});
+
+// Attention is gated by coherence energy
+const result = cgtAttention.compute(query, keys, values);
+console.log('Coherence energy:', result.energy);
+console.log('Is coherent:', result.isCoherent);
+```
+
+**Key features:**
+- Energy-weighted attention: Lower coherence energy → higher attention
+- Automatic hallucination detection via residual analysis
+- GPU-accelerated with wgpu WGSL shaders (vec4 optimized)
+- SIMD fallback (AVX-512/AVX2/NEON)
+
+### Training
+
+- `InfoNCELoss` - Contrastive loss function
+- `Adam` - Adam optimizer
+- `AdamW` - AdamW optimizer with weight decay
+- `LRScheduler` - Learning rate scheduler
+
+### Utilities
+
+- `utils.cosineSimilarity()` - Cosine similarity between vectors
+- `utils.l2Norm()` - L2 norm of a vector
+- `utils.normalize()` - Normalize vector to unit length
+- `utils.softmax()` - Apply softmax transformation
+- `utils.attentionWeights()` - Compute attention weights from scores
+- `utils.batchNormalize()` - Batch normalization
+- `utils.randomOrthogonalMatrix()` - Generate random orthogonal matrix
+- `utils.pairwiseDistances()` - Compute pairwise distances
+
+## Performance
+
+The WASM bindings provide near-native performance for attention computations:
+
+- Optimized with `opt-level = "s"` and LTO
+- SIMD acceleration where available
+- Efficient memory management
+- Zero-copy data transfer where possible
+
+## License
+
+MIT OR Apache-2.0
diff --git a/crates/ruvector-attention-wasm/pkg/package.json b/crates/ruvector-attention-wasm/pkg/package.json
new file mode 100644
index 00000000..7500bb8a
--- /dev/null
+++ b/crates/ruvector-attention-wasm/pkg/package.json
@@ -0,0 +1,28 @@
+{
+  "name": "ruvector-attention-wasm",
+  "collaborators": [
+    "Ruvector Team"
+  ],
+  "description": "High-performance WebAssembly attention mechanisms: Multi-Head, Flash, Hyperbolic, MoE, CGT Sheaf Attention with GPU acceleration for transformers and LLMs",
+  "version": "2.0.5",
+  "license": "MIT",
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/ruvnet/ruvector"
+  },
+  "files": [
+    "ruvector_attention_wasm_bg.wasm",
+    "ruvector_attention_wasm.js",
+    "ruvector_attention_wasm.d.ts"
+  ],
+  "main": "ruvector_attention_wasm.js",
+  "homepage": "https://ruv.io/ruvector",
+  "types": "ruvector_attention_wasm.d.ts",
+  "keywords": [
+    "wasm",
+    "attention",
+    "transformer",
+    "flash-attention",
+    "llm"
+  ]
+}
\ No newline at end of file
diff --git a/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm.d.ts b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm.d.ts
new file mode 100644
index 00000000..90c7dc99
--- /dev/null
+++ b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm.d.ts
@@ -0,0 +1,359 @@
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * Adam optimizer
+ */
+export class WasmAdam {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Create a new Adam optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     */
+    constructor(param_count: number, learning_rate: number);
+    /**
+     * Reset optimizer state
+     */
+    reset(): void;
+    /**
+     * Perform optimization step
+     *
+     * # Arguments
+     * * `params` - Current parameter values (will be updated in-place)
+     * * `gradients` - Gradient values
+     */
+    step(params: Float32Array, gradients: Float32Array): void;
+    /**
+     * Get current learning rate
+     */
+    learning_rate: number;
+}
+
+/**
+ * AdamW optimizer (Adam with decoupled weight decay)
+ */
+export class WasmAdamW {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Create a new AdamW optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `weight_decay` - Weight decay coefficient
+     */
+    constructor(param_count: number, learning_rate: number, weight_decay: number);
+    /**
+     * Reset optimizer state
+     */
+    reset(): void;
+    /**
+     * Perform optimization step with weight decay
+     */
+    step(params: Float32Array, gradients: Float32Array): void;
+    /**
+     * Get current learning rate
+     */
+    learning_rate: number;
+    /**
+     * Get weight decay
+     */
+    readonly weight_decay: number;
+}
+
+/**
+ * Flash attention mechanism
+ */
+export class WasmFlashAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute flash attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new flash attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `block_size` - Block size for tiling
+     */
+    constructor(dim: number, block_size: number);
+}
+
+/**
+ * Hyperbolic attention mechanism
+ */
+export class WasmHyperbolicAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute hyperbolic attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new hyperbolic attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `curvature` - Hyperbolic curvature parameter
+     */
+    constructor(dim: number, curvature: number);
+    /**
+     * Get the curvature
+     */
+    readonly curvature: number;
+}
+
+/**
+ * InfoNCE contrastive loss for training
+ */
+export class WasmInfoNCELoss {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute InfoNCE loss
+     *
+     * # Arguments
+     * * `anchor` - Anchor embedding
+     * * `positive` - Positive example embedding
+     * * `negatives` - Array of negative example embeddings
+     */
+    compute(anchor: Float32Array, positive: Float32Array, negatives: any): number;
+    /**
+     * Create a new InfoNCE loss instance
+     *
+     * # Arguments
+     * * `temperature` - Temperature parameter for softmax
+     */
+    constructor(temperature: number);
+}
+
+/**
+ * Learning rate scheduler
+ */
+export class WasmLRScheduler {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Get learning rate for current step
+     */
+    get_lr(): number;
+    /**
+     * Create a new learning rate scheduler with warmup and cosine decay
+     *
+     * # Arguments
+     * * `initial_lr` - Initial learning rate
+     * * `warmup_steps` - Number of warmup steps
+     * * `total_steps` - Total training steps
+     */
+    constructor(initial_lr: number, warmup_steps: number, total_steps: number);
+    /**
+     * Reset scheduler
+     */
+    reset(): void;
+    /**
+     * Advance to next step
+     */
+    step(): void;
+}
+
+/**
+ * Linear attention (Performer-style)
+ */
+export class WasmLinearAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute linear attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new linear attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_features` - Number of random features
+     */
+    constructor(dim: number, num_features: number);
+}
+
+/**
+ * Local-global attention mechanism
+ */
+export class WasmLocalGlobalAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute local-global attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new local-global attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `local_window` - Size of local attention window
+     * * `global_tokens` - Number of global attention tokens
+     */
+    constructor(dim: number, local_window: number, global_tokens: number);
+}
+
+/**
+ * Mixture of Experts (MoE) attention
+ */
+export class WasmMoEAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute MoE attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new MoE attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_experts` - Number of expert attention mechanisms
+     * * `top_k` - Number of experts to use per query
+     */
+    constructor(dim: number, num_experts: number, top_k: number);
+}
+
+/**
+ * Multi-head attention mechanism
+ */
+export class WasmMultiHeadAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute multi-head attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new multi-head attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_heads` - Number of attention heads
+     */
+    constructor(dim: number, num_heads: number);
+    /**
+     * Get the dimension
+     */
+    readonly dim: number;
+    /**
+     * Get the number of heads
+     */
+    readonly num_heads: number;
+}
+
+/**
+ * SGD optimizer with momentum
+ */
+export class WasmSGD {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Create a new SGD optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `momentum` - Momentum coefficient (default: 0)
+     */
+    constructor(param_count: number, learning_rate: number, momentum?: number | null);
+    /**
+     * Reset optimizer state
+     */
+    reset(): void;
+    /**
+     * Perform optimization step
+     */
+    step(params: Float32Array, gradients: Float32Array): void;
+    /**
+     * Get current learning rate
+     */
+    learning_rate: number;
+}
+
+/**
+ * Compute attention weights from scores
+ */
+export function attention_weights(scores: Float32Array, temperature?: number | null): void;
+
+/**
+ * Get information about available attention mechanisms
+ */
+export function available_mechanisms(): any;
+
+/**
+ * Batch normalize vectors
+ */
+export function batch_normalize(vectors: any, epsilon?: number | null): Float32Array;
+
+/**
+ * Compute cosine similarity between two vectors
+ */
+export function cosine_similarity(a: Float32Array, b: Float32Array): number;
+
+/**
+ * Initialize the WASM module with panic hook
+ */
+export function init(): void;
+
+/**
+ * Compute L2 norm of a vector
+ */
+export function l2_norm(vec: Float32Array): number;
+
+/**
+ * Log a message to the browser console
+ */
+export function log(message: string): void;
+
+/**
+ * Log an error to the browser console
+ */
+export function log_error(message: string): void;
+
+/**
+ * Normalize a vector to unit length
+ */
+export function normalize(vec: Float32Array): void;
+
+/**
+ * Compute pairwise distances between vectors
+ */
+export function pairwise_distances(vectors: any): Float32Array;
+
+/**
+ * Generate random orthogonal matrix (for initialization)
+ */
+export function random_orthogonal_matrix(dim: number): Float32Array;
+
+/**
+ * Compute scaled dot-product attention
+ *
+ * # Arguments
+ * * `query` - Query vector as Float32Array
+ * * `keys` - Array of key vectors
+ * * `values` - Array of value vectors
+ * * `scale` - Optional scaling factor (defaults to 1/sqrt(dim))
+ */
+export function scaled_dot_attention(query: Float32Array, keys: any, values: any, scale?: number | null): Float32Array;
+
+/**
+ * Compute softmax of a vector
+ */
+export function softmax(vec: Float32Array): void;
+
+/**
+ * Get the version of the ruvector-attention-wasm crate
+ */
+export function version(): string;
diff --git a/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm.js b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm.js
new file mode 100644
index 00000000..875532dc
--- /dev/null
+++ b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm.js
@@ -0,0 +1,1417 @@
+/* @ts-self-types="./ruvector_attention_wasm.d.ts" */
+
+/**
+ * Adam optimizer
+ */
+class WasmAdam {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmAdamFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmadam_free(ptr, 0);
+    }
+    /**
+     * Get current learning rate
+     * @returns {number}
+     */
+    get learning_rate() {
+        const ret = wasm.wasmadam_learning_rate(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new Adam optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * @param {number} param_count
+     * @param {number} learning_rate
+     */
+    constructor(param_count, learning_rate) {
+        const ret = wasm.wasmadam_new(param_count, learning_rate);
+        this.__wbg_ptr = ret >>> 0;
+        WasmAdamFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset optimizer state
+     */
+    reset() {
+        wasm.wasmadam_reset(this.__wbg_ptr);
+    }
+    /**
+     * Set learning rate
+     * @param {number} lr
+     */
+    set learning_rate(lr) {
+        wasm.wasmadam_set_learning_rate(this.__wbg_ptr, lr);
+    }
+    /**
+     * Perform optimization step
+     *
+     * # Arguments
+     * * `params` - Current parameter values (will be updated in-place)
+     * * `gradients` - Gradient values
+     * @param {Float32Array} params
+     * @param {Float32Array} gradients
+     */
+    step(params, gradients) {
+        var ptr0 = passArrayF32ToWasm0(params, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(gradients, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.wasmadam_step(this.__wbg_ptr, ptr0, len0, addHeapObject(params), ptr1, len1);
+    }
+}
+if (Symbol.dispose) WasmAdam.prototype[Symbol.dispose] = WasmAdam.prototype.free;
+exports.WasmAdam = WasmAdam;
+
+/**
+ * AdamW optimizer (Adam with decoupled weight decay)
+ */
+class WasmAdamW {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmAdamWFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmadamw_free(ptr, 0);
+    }
+    /**
+     * Get current learning rate
+     * @returns {number}
+     */
+    get learning_rate() {
+        const ret = wasm.wasmadamw_learning_rate(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new AdamW optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `weight_decay` - Weight decay coefficient
+     * @param {number} param_count
+     * @param {number} learning_rate
+     * @param {number} weight_decay
+     */
+    constructor(param_count, learning_rate, weight_decay) {
+        const ret = wasm.wasmadamw_new(param_count, learning_rate, weight_decay);
+        this.__wbg_ptr = ret >>> 0;
+        WasmAdamWFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset optimizer state
+     */
+    reset() {
+        wasm.wasmadamw_reset(this.__wbg_ptr);
+    }
+    /**
+     * Set learning rate
+     * @param {number} lr
+     */
+    set learning_rate(lr) {
+        wasm.wasmadamw_set_learning_rate(this.__wbg_ptr, lr);
+    }
+    /**
+     * Perform optimization step with weight decay
+     * @param {Float32Array} params
+     * @param {Float32Array} gradients
+     */
+    step(params, gradients) {
+        var ptr0 = passArrayF32ToWasm0(params, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(gradients, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.wasmadamw_step(this.__wbg_ptr, ptr0, len0, addHeapObject(params), ptr1, len1);
+    }
+    /**
+     * Get weight decay
+     * @returns {number}
+     */
+    get weight_decay() {
+        const ret = wasm.wasmadamw_weight_decay(this.__wbg_ptr);
+        return ret;
+    }
+}
+if (Symbol.dispose) WasmAdamW.prototype[Symbol.dispose] = WasmAdamW.prototype.free;
+exports.WasmAdamW = WasmAdamW;
+
+/**
+ * Flash attention mechanism
+ */
+class WasmFlashAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmFlashAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmflashattention_free(ptr, 0);
+    }
+    /**
+     * Compute flash attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmflashattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new flash attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `block_size` - Block size for tiling
+     * @param {number} dim
+     * @param {number} block_size
+     */
+    constructor(dim, block_size) {
+        const ret = wasm.wasmflashattention_new(dim, block_size);
+        this.__wbg_ptr = ret >>> 0;
+        WasmFlashAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmFlashAttention.prototype[Symbol.dispose] = WasmFlashAttention.prototype.free;
+exports.WasmFlashAttention = WasmFlashAttention;
+
+/**
+ * Hyperbolic attention mechanism
+ */
+class WasmHyperbolicAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmHyperbolicAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmhyperbolicattention_free(ptr, 0);
+    }
+    /**
+     * Compute hyperbolic attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmhyperbolicattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Get the curvature
+     * @returns {number}
+     */
+    get curvature() {
+        const ret = wasm.wasmhyperbolicattention_curvature(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new hyperbolic attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `curvature` - Hyperbolic curvature parameter
+     * @param {number} dim
+     * @param {number} curvature
+     */
+    constructor(dim, curvature) {
+        const ret = wasm.wasmhyperbolicattention_new(dim, curvature);
+        this.__wbg_ptr = ret >>> 0;
+        WasmHyperbolicAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmHyperbolicAttention.prototype[Symbol.dispose] = WasmHyperbolicAttention.prototype.free;
+exports.WasmHyperbolicAttention = WasmHyperbolicAttention;
+
+/**
+ * InfoNCE contrastive loss for training
+ */
+class WasmInfoNCELoss {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmInfoNCELossFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasminfonceloss_free(ptr, 0);
+    }
+    /**
+     * Compute InfoNCE loss
+     *
+     * # Arguments
+     * * `anchor` - Anchor embedding
+     * * `positive` - Positive example embedding
+     * * `negatives` - Array of negative example embeddings
+     * @param {Float32Array} anchor
+     * @param {Float32Array} positive
+     * @param {any} negatives
+     * @returns {number}
+     */
+    compute(anchor, positive, negatives) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(anchor, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            const ptr1 = passArrayF32ToWasm0(positive, wasm.__wbindgen_export);
+            const len1 = WASM_VECTOR_LEN;
+            wasm.wasminfonceloss_compute(retptr, this.__wbg_ptr, ptr0, len0, ptr1, len1, addHeapObject(negatives));
+            var r0 = getDataViewMemory0().getFloat32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            if (r2) {
+                throw takeObject(r1);
+            }
+            return r0;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new InfoNCE loss instance
+     *
+     * # Arguments
+     * * `temperature` - Temperature parameter for softmax
+     * @param {number} temperature
+     */
+    constructor(temperature) {
+        const ret = wasm.wasminfonceloss_new(temperature);
+        this.__wbg_ptr = ret >>> 0;
+        WasmInfoNCELossFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmInfoNCELoss.prototype[Symbol.dispose] = WasmInfoNCELoss.prototype.free;
+exports.WasmInfoNCELoss = WasmInfoNCELoss;
+
+/**
+ * Learning rate scheduler
+ */
+class WasmLRScheduler {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmLRSchedulerFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmlrscheduler_free(ptr, 0);
+    }
+    /**
+     * Get learning rate for current step
+     * @returns {number}
+     */
+    get_lr() {
+        const ret = wasm.wasmlrscheduler_get_lr(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new learning rate scheduler with warmup and cosine decay
+     *
+     * # Arguments
+     * * `initial_lr` - Initial learning rate
+     * * `warmup_steps` - Number of warmup steps
+     * * `total_steps` - Total training steps
+     * @param {number} initial_lr
+     * @param {number} warmup_steps
+     * @param {number} total_steps
+     */
+    constructor(initial_lr, warmup_steps, total_steps) {
+        const ret = wasm.wasmlrscheduler_new(initial_lr, warmup_steps, total_steps);
+        this.__wbg_ptr = ret >>> 0;
+        WasmLRSchedulerFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset scheduler
+     */
+    reset() {
+        wasm.wasmlrscheduler_reset(this.__wbg_ptr);
+    }
+    /**
+     * Advance to next step
+     */
+    step() {
+        wasm.wasmlrscheduler_step(this.__wbg_ptr);
+    }
+}
+if (Symbol.dispose) WasmLRScheduler.prototype[Symbol.dispose] = WasmLRScheduler.prototype.free;
+exports.WasmLRScheduler = WasmLRScheduler;
+
+/**
+ * Linear attention (Performer-style)
+ */
+class WasmLinearAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmLinearAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmlinearattention_free(ptr, 0);
+    }
+    /**
+     * Compute linear attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmlinearattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new linear attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_features` - Number of random features
+     * @param {number} dim
+     * @param {number} num_features
+     */
+    constructor(dim, num_features) {
+        const ret = wasm.wasmlinearattention_new(dim, num_features);
+        this.__wbg_ptr = ret >>> 0;
+        WasmLinearAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmLinearAttention.prototype[Symbol.dispose] = WasmLinearAttention.prototype.free;
+exports.WasmLinearAttention = WasmLinearAttention;
+
+/**
+ * Local-global attention mechanism
+ */
+class WasmLocalGlobalAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmLocalGlobalAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmlocalglobalattention_free(ptr, 0);
+    }
+    /**
+     * Compute local-global attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmlocalglobalattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new local-global attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `local_window` - Size of local attention window
+     * * `global_tokens` - Number of global attention tokens
+     * @param {number} dim
+     * @param {number} local_window
+     * @param {number} global_tokens
+     */
+    constructor(dim, local_window, global_tokens) {
+        const ret = wasm.wasmlocalglobalattention_new(dim, local_window, global_tokens);
+        this.__wbg_ptr = ret >>> 0;
+        WasmLocalGlobalAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmLocalGlobalAttention.prototype[Symbol.dispose] = WasmLocalGlobalAttention.prototype.free;
+exports.WasmLocalGlobalAttention = WasmLocalGlobalAttention;
+
+/**
+ * Mixture of Experts (MoE) attention
+ */
+class WasmMoEAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmMoEAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmmoeattention_free(ptr, 0);
+    }
+    /**
+     * Compute MoE attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmmoeattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new MoE attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_experts` - Number of expert attention mechanisms
+     * * `top_k` - Number of experts to use per query
+     * @param {number} dim
+     * @param {number} num_experts
+     * @param {number} top_k
+     */
+    constructor(dim, num_experts, top_k) {
+        const ret = wasm.wasmmoeattention_new(dim, num_experts, top_k);
+        this.__wbg_ptr = ret >>> 0;
+        WasmMoEAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmMoEAttention.prototype[Symbol.dispose] = WasmMoEAttention.prototype.free;
+exports.WasmMoEAttention = WasmMoEAttention;
+
+/**
+ * Multi-head attention mechanism
+ */
+class WasmMultiHeadAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmMultiHeadAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmmultiheadattention_free(ptr, 0);
+    }
+    /**
+     * Compute multi-head attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmmultiheadattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Get the dimension
+     * @returns {number}
+     */
+    get dim() {
+        const ret = wasm.wasmmultiheadattention_dim(this.__wbg_ptr);
+        return ret >>> 0;
+    }
+    /**
+     * Create a new multi-head attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_heads` - Number of attention heads
+     * @param {number} dim
+     * @param {number} num_heads
+     */
+    constructor(dim, num_heads) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            wasm.wasmmultiheadattention_new(retptr, dim, num_heads);
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            if (r2) {
+                throw takeObject(r1);
+            }
+            this.__wbg_ptr = r0 >>> 0;
+            WasmMultiHeadAttentionFinalization.register(this, this.__wbg_ptr, this);
+            return this;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Get the number of heads
+     * @returns {number}
+     */
+    get num_heads() {
+        const ret = wasm.wasmmultiheadattention_num_heads(this.__wbg_ptr);
+        return ret >>> 0;
+    }
+}
+if (Symbol.dispose) WasmMultiHeadAttention.prototype[Symbol.dispose] = WasmMultiHeadAttention.prototype.free;
+exports.WasmMultiHeadAttention = WasmMultiHeadAttention;
+
+/**
+ * SGD optimizer with momentum
+ */
+class WasmSGD {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmSGDFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmsgd_free(ptr, 0);
+    }
+    /**
+     * Get current learning rate
+     * @returns {number}
+     */
+    get learning_rate() {
+        const ret = wasm.wasmsgd_learning_rate(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new SGD optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `momentum` - Momentum coefficient (default: 0)
+     * @param {number} param_count
+     * @param {number} learning_rate
+     * @param {number | null} [momentum]
+     */
+    constructor(param_count, learning_rate, momentum) {
+        const ret = wasm.wasmsgd_new(param_count, learning_rate, isLikeNone(momentum) ? 0x100000001 : Math.fround(momentum));
+        this.__wbg_ptr = ret >>> 0;
+        WasmSGDFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset optimizer state
+     */
+    reset() {
+        wasm.wasmsgd_reset(this.__wbg_ptr);
+    }
+    /**
+     * Set learning rate
+     * @param {number} lr
+     */
+    set learning_rate(lr) {
+        wasm.wasmsgd_set_learning_rate(this.__wbg_ptr, lr);
+    }
+    /**
+     * Perform optimization step
+     * @param {Float32Array} params
+     * @param {Float32Array} gradients
+     */
+    step(params, gradients) {
+        var ptr0 = passArrayF32ToWasm0(params, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(gradients, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.wasmsgd_step(this.__wbg_ptr, ptr0, len0, addHeapObject(params), ptr1, len1);
+    }
+}
+if (Symbol.dispose) WasmSGD.prototype[Symbol.dispose] = WasmSGD.prototype.free;
+exports.WasmSGD = WasmSGD;
+
+/**
+ * Compute attention weights from scores
+ * @param {Float32Array} scores
+ * @param {number | null} [temperature]
+ */
+function attention_weights(scores, temperature) {
+    var ptr0 = passArrayF32ToWasm0(scores, wasm.__wbindgen_export);
+    var len0 = WASM_VECTOR_LEN;
+    wasm.attention_weights(ptr0, len0, addHeapObject(scores), isLikeNone(temperature) ? 0x100000001 : Math.fround(temperature));
+}
+exports.attention_weights = attention_weights;
+
+/**
+ * Get information about available attention mechanisms
+ * @returns {any}
+ */
+function available_mechanisms() {
+    const ret = wasm.available_mechanisms();
+    return takeObject(ret);
+}
+exports.available_mechanisms = available_mechanisms;
+
+/**
+ * Batch normalize vectors
+ * @param {any} vectors
+ * @param {number | null} [epsilon]
+ * @returns {Float32Array}
+ */
+function batch_normalize(vectors, epsilon) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.batch_normalize(retptr, addHeapObject(vectors), isLikeNone(epsilon) ? 0x100000001 : Math.fround(epsilon));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+        if (r3) {
+            throw takeObject(r2);
+        }
+        var v1 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v1;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.batch_normalize = batch_normalize;
+
+/**
+ * Compute cosine similarity between two vectors
+ * @param {Float32Array} a
+ * @param {Float32Array} b
+ * @returns {number}
+ */
+function cosine_similarity(a, b) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        const ptr0 = passArrayF32ToWasm0(a, wasm.__wbindgen_export);
+        const len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(b, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.cosine_similarity(retptr, ptr0, len0, ptr1, len1);
+        var r0 = getDataViewMemory0().getFloat32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        if (r2) {
+            throw takeObject(r1);
+        }
+        return r0;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.cosine_similarity = cosine_similarity;
+
+/**
+ * Initialize the WASM module with panic hook
+ */
+function init() {
+    wasm.init();
+}
+exports.init = init;
+
+/**
+ * Compute L2 norm of a vector
+ * @param {Float32Array} vec
+ * @returns {number}
+ */
+function l2_norm(vec) {
+    const ptr0 = passArrayF32ToWasm0(vec, wasm.__wbindgen_export);
+    const len0 = WASM_VECTOR_LEN;
+    const ret = wasm.l2_norm(ptr0, len0);
+    return ret;
+}
+exports.l2_norm = l2_norm;
+
+/**
+ * Log a message to the browser console
+ * @param {string} message
+ */
+function log(message) {
+    const ptr0 = passStringToWasm0(message, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+    const len0 = WASM_VECTOR_LEN;
+    wasm.log(ptr0, len0);
+}
+exports.log = log;
+
+/**
+ * Log an error to the browser console
+ * @param {string} message
+ */
+function log_error(message) {
+    const ptr0 = passStringToWasm0(message, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+    const len0 = WASM_VECTOR_LEN;
+    wasm.log_error(ptr0, len0);
+}
+exports.log_error = log_error;
+
+/**
+ * Normalize a vector to unit length
+ * @param {Float32Array} vec
+ */
+function normalize(vec) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        var ptr0 = passArrayF32ToWasm0(vec, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        wasm.normalize(retptr, ptr0, len0, addHeapObject(vec));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        if (r1) {
+            throw takeObject(r0);
+        }
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.normalize = normalize;
+
+/**
+ * Compute pairwise distances between vectors
+ * @param {any} vectors
+ * @returns {Float32Array}
+ */
+function pairwise_distances(vectors) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.pairwise_distances(retptr, addHeapObject(vectors));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+        if (r3) {
+            throw takeObject(r2);
+        }
+        var v1 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v1;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.pairwise_distances = pairwise_distances;
+
+/**
+ * Generate random orthogonal matrix (for initialization)
+ * @param {number} dim
+ * @returns {Float32Array}
+ */
+function random_orthogonal_matrix(dim) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.random_orthogonal_matrix(retptr, dim);
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var v1 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v1;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.random_orthogonal_matrix = random_orthogonal_matrix;
+
+/**
+ * Compute scaled dot-product attention
+ *
+ * # Arguments
+ * * `query` - Query vector as Float32Array
+ * * `keys` - Array of key vectors
+ * * `values` - Array of value vectors
+ * * `scale` - Optional scaling factor (defaults to 1/sqrt(dim))
+ * @param {Float32Array} query
+ * @param {any} keys
+ * @param {any} values
+ * @param {number | null} [scale]
+ * @returns {Float32Array}
+ */
+function scaled_dot_attention(query, keys, values, scale) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+        const len0 = WASM_VECTOR_LEN;
+        wasm.scaled_dot_attention(retptr, ptr0, len0, addHeapObject(keys), addHeapObject(values), isLikeNone(scale) ? 0x100000001 : Math.fround(scale));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+        if (r3) {
+            throw takeObject(r2);
+        }
+        var v2 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v2;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.scaled_dot_attention = scaled_dot_attention;
+
+/**
+ * Compute softmax of a vector
+ * @param {Float32Array} vec
+ */
+function softmax(vec) {
+    var ptr0 = passArrayF32ToWasm0(vec, wasm.__wbindgen_export);
+    var len0 = WASM_VECTOR_LEN;
+    wasm.softmax(ptr0, len0, addHeapObject(vec));
+}
+exports.softmax = softmax;
+
+/**
+ * Get the version of the ruvector-attention-wasm crate
+ * @returns {string}
+ */
+function version() {
+    let deferred1_0;
+    let deferred1_1;
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.version(retptr);
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        deferred1_0 = r0;
+        deferred1_1 = r1;
+        return getStringFromWasm0(r0, r1);
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+        wasm.__wbindgen_export4(deferred1_0, deferred1_1, 1);
+    }
+}
+exports.version = version;
+
+function __wbg_get_imports() {
+    const import0 = {
+        __proto__: null,
+        __wbg_Error_4577686b3a6d9b3a: function(arg0, arg1) {
+            const ret = Error(getStringFromWasm0(arg0, arg1));
+            return addHeapObject(ret);
+        },
+        __wbg_String_8564e559799eccda: function(arg0, arg1) {
+            const ret = String(getObject(arg1));
+            const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            const len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg___wbindgen_boolean_get_18c4ed9422296fff: function(arg0) {
+            const v = getObject(arg0);
+            const ret = typeof(v) === 'boolean' ? v : undefined;
+            return isLikeNone(ret) ? 0xFFFFFF : ret ? 1 : 0;
+        },
+        __wbg___wbindgen_copy_to_typed_array_5294f8e46aecc086: function(arg0, arg1, arg2) {
+            new Uint8Array(getObject(arg2).buffer, getObject(arg2).byteOffset, getObject(arg2).byteLength).set(getArrayU8FromWasm0(arg0, arg1));
+        },
+        __wbg___wbindgen_debug_string_ddde1867f49c2442: function(arg0, arg1) {
+            const ret = debugString(getObject(arg1));
+            const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            const len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg___wbindgen_is_function_d633e708baf0d146: function(arg0) {
+            const ret = typeof(getObject(arg0)) === 'function';
+            return ret;
+        },
+        __wbg___wbindgen_is_object_4b3de556756ee8a8: function(arg0) {
+            const val = getObject(arg0);
+            const ret = typeof(val) === 'object' && val !== null;
+            return ret;
+        },
+        __wbg___wbindgen_jsval_loose_eq_1562ceb9af84e990: function(arg0, arg1) {
+            const ret = getObject(arg0) == getObject(arg1);
+            return ret;
+        },
+        __wbg___wbindgen_number_get_5854912275df1894: function(arg0, arg1) {
+            const obj = getObject(arg1);
+            const ret = typeof(obj) === 'number' ? obj : undefined;
+            getDataViewMemory0().setFloat64(arg0 + 8 * 1, isLikeNone(ret) ? 0 : ret, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, !isLikeNone(ret), true);
+        },
+        __wbg___wbindgen_string_get_3e5751597f39a112: function(arg0, arg1) {
+            const obj = getObject(arg1);
+            const ret = typeof(obj) === 'string' ? obj : undefined;
+            var ptr1 = isLikeNone(ret) ? 0 : passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            var len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg___wbindgen_throw_39bc967c0e5a9b58: function(arg0, arg1) {
+            throw new Error(getStringFromWasm0(arg0, arg1));
+        },
+        __wbg_call_73af281463ec8b58: function() { return handleError(function (arg0, arg1) {
+            const ret = getObject(arg0).call(getObject(arg1));
+            return addHeapObject(ret);
+        }, arguments); },
+        __wbg_done_5aad55ec6b1954b1: function(arg0) {
+            const ret = getObject(arg0).done;
+            return ret;
+        },
+        __wbg_error_a6fa202b58aa1cd3: function(arg0, arg1) {
+            let deferred0_0;
+            let deferred0_1;
+            try {
+                deferred0_0 = arg0;
+                deferred0_1 = arg1;
+                console.error(getStringFromWasm0(arg0, arg1));
+            } finally {
+                wasm.__wbindgen_export4(deferred0_0, deferred0_1, 1);
+            }
+        },
+        __wbg_error_ad28debb48b5c6bb: function(arg0) {
+            console.error(getObject(arg0));
+        },
+        __wbg_get_4920fefd3451364b: function() { return handleError(function (arg0, arg1) {
+            const ret = Reflect.get(getObject(arg0), getObject(arg1));
+            return addHeapObject(ret);
+        }, arguments); },
+        __wbg_get_unchecked_3d0f4b91c8eca4f0: function(arg0, arg1) {
+            const ret = getObject(arg0)[arg1 >>> 0];
+            return addHeapObject(ret);
+        },
+        __wbg_instanceof_ArrayBuffer_15859862b80b732d: function(arg0) {
+            let result;
+            try {
+                result = getObject(arg0) instanceof ArrayBuffer;
+            } catch (_) {
+                result = false;
+            }
+            const ret = result;
+            return ret;
+        },
+        __wbg_instanceof_Uint8Array_2240b7046ac16f05: function(arg0) {
+            let result;
+            try {
+                result = getObject(arg0) instanceof Uint8Array;
+            } catch (_) {
+                result = false;
+            }
+            const ret = result;
+            return ret;
+        },
+        __wbg_isArray_fad08a0d12828686: function(arg0) {
+            const ret = Array.isArray(getObject(arg0));
+            return ret;
+        },
+        __wbg_iterator_fc7ad8d33bab9e26: function() {
+            const ret = Symbol.iterator;
+            return addHeapObject(ret);
+        },
+        __wbg_length_5855c1f289dfffc1: function(arg0) {
+            const ret = getObject(arg0).length;
+            return ret;
+        },
+        __wbg_length_a31e05262e09b7f8: function(arg0) {
+            const ret = getObject(arg0).length;
+            return ret;
+        },
+        __wbg_log_3c5e4b64af29e724: function(arg0) {
+            console.log(getObject(arg0));
+        },
+        __wbg_new_09959f7b4c92c246: function(arg0) {
+            const ret = new Uint8Array(getObject(arg0));
+            return addHeapObject(ret);
+        },
+        __wbg_new_227d7c05414eb861: function() {
+            const ret = new Error();
+            return addHeapObject(ret);
+        },
+        __wbg_new_cbee8c0d5c479eac: function() {
+            const ret = new Array();
+            return addHeapObject(ret);
+        },
+        __wbg_next_a5fe6f328f7affc2: function(arg0) {
+            const ret = getObject(arg0).next;
+            return addHeapObject(ret);
+        },
+        __wbg_next_e592122bb4ed4c67: function() { return handleError(function (arg0) {
+            const ret = getObject(arg0).next();
+            return addHeapObject(ret);
+        }, arguments); },
+        __wbg_prototypesetcall_f034d444741426c3: function(arg0, arg1, arg2) {
+            Uint8Array.prototype.set.call(getArrayU8FromWasm0(arg0, arg1), getObject(arg2));
+        },
+        __wbg_random_2b7bed8995d680fb: function() {
+            const ret = Math.random();
+            return ret;
+        },
+        __wbg_set_4c81cfb5dc3a333c: function(arg0, arg1, arg2) {
+            getObject(arg0)[arg1 >>> 0] = takeObject(arg2);
+        },
+        __wbg_stack_3b0d974bbf31e44f: function(arg0, arg1) {
+            const ret = getObject(arg1).stack;
+            const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            const len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg_value_667dcb90597486a6: function(arg0) {
+            const ret = getObject(arg0).value;
+            return addHeapObject(ret);
+        },
+        __wbindgen_cast_0000000000000001: function(arg0, arg1) {
+            // Cast intrinsic for `Ref(String) -> Externref`.
+            const ret = getStringFromWasm0(arg0, arg1);
+            return addHeapObject(ret);
+        },
+        __wbindgen_object_drop_ref: function(arg0) {
+            takeObject(arg0);
+        },
+    };
+    return {
+        __proto__: null,
+        "./ruvector_attention_wasm_bg.js": import0,
+    };
+}
+
+const WasmAdamFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmadam_free(ptr >>> 0, 1));
+const WasmAdamWFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmadamw_free(ptr >>> 0, 1));
+const WasmFlashAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmflashattention_free(ptr >>> 0, 1));
+const WasmHyperbolicAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmhyperbolicattention_free(ptr >>> 0, 1));
+const WasmInfoNCELossFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasminfonceloss_free(ptr >>> 0, 1));
+const WasmLRSchedulerFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmlrscheduler_free(ptr >>> 0, 1));
+const WasmLinearAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmlinearattention_free(ptr >>> 0, 1));
+const WasmLocalGlobalAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmlocalglobalattention_free(ptr >>> 0, 1));
+const WasmMoEAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmmoeattention_free(ptr >>> 0, 1));
+const WasmMultiHeadAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmmultiheadattention_free(ptr >>> 0, 1));
+const WasmSGDFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmsgd_free(ptr >>> 0, 1));
+
+function addHeapObject(obj) {
+    if (heap_next === heap.length) heap.push(heap.length + 1);
+    const idx = heap_next;
+    heap_next = heap[idx];
+
+    heap[idx] = obj;
+    return idx;
+}
+
+function debugString(val) {
+    // primitive types
+    const type = typeof val;
+    if (type == 'number' || type == 'boolean' || val == null) {
+        return  `${val}`;
+    }
+    if (type == 'string') {
+        return `"${val}"`;
+    }
+    if (type == 'symbol') {
+        const description = val.description;
+        if (description == null) {
+            return 'Symbol';
+        } else {
+            return `Symbol(${description})`;
+        }
+    }
+    if (type == 'function') {
+        const name = val.name;
+        if (typeof name == 'string' && name.length > 0) {
+            return `Function(${name})`;
+        } else {
+            return 'Function';
+        }
+    }
+    // objects
+    if (Array.isArray(val)) {
+        const length = val.length;
+        let debug = '[';
+        if (length > 0) {
+            debug += debugString(val[0]);
+        }
+        for(let i = 1; i < length; i++) {
+            debug += ', ' + debugString(val[i]);
+        }
+        debug += ']';
+        return debug;
+    }
+    // Test for built-in
+    const builtInMatches = /\[object ([^\]]+)\]/.exec(toString.call(val));
+    let className;
+    if (builtInMatches && builtInMatches.length > 1) {
+        className = builtInMatches[1];
+    } else {
+        // Failed to match the standard '[object ClassName]'
+        return toString.call(val);
+    }
+    if (className == 'Object') {
+        // we're a user defined class or Object
+        // JSON.stringify avoids problems with cycles, and is generally much
+        // easier than looping through ownProperties of `val`.
+        try {
+            return 'Object(' + JSON.stringify(val) + ')';
+        } catch (_) {
+            return 'Object';
+        }
+    }
+    // errors
+    if (val instanceof Error) {
+        return `${val.name}: ${val.message}\n${val.stack}`;
+    }
+    // TODO we could test for more things here, like `Set`s and `Map`s.
+    return className;
+}
+
+function dropObject(idx) {
+    if (idx < 1028) return;
+    heap[idx] = heap_next;
+    heap_next = idx;
+}
+
+function getArrayF32FromWasm0(ptr, len) {
+    ptr = ptr >>> 0;
+    return getFloat32ArrayMemory0().subarray(ptr / 4, ptr / 4 + len);
+}
+
+function getArrayU8FromWasm0(ptr, len) {
+    ptr = ptr >>> 0;
+    return getUint8ArrayMemory0().subarray(ptr / 1, ptr / 1 + len);
+}
+
+let cachedDataViewMemory0 = null;
+function getDataViewMemory0() {
+    if (cachedDataViewMemory0 === null || cachedDataViewMemory0.buffer.detached === true || (cachedDataViewMemory0.buffer.detached === undefined && cachedDataViewMemory0.buffer !== wasm.memory.buffer)) {
+        cachedDataViewMemory0 = new DataView(wasm.memory.buffer);
+    }
+    return cachedDataViewMemory0;
+}
+
+let cachedFloat32ArrayMemory0 = null;
+function getFloat32ArrayMemory0() {
+    if (cachedFloat32ArrayMemory0 === null || cachedFloat32ArrayMemory0.byteLength === 0) {
+        cachedFloat32ArrayMemory0 = new Float32Array(wasm.memory.buffer);
+    }
+    return cachedFloat32ArrayMemory0;
+}
+
+function getStringFromWasm0(ptr, len) {
+    ptr = ptr >>> 0;
+    return decodeText(ptr, len);
+}
+
+let cachedUint8ArrayMemory0 = null;
+function getUint8ArrayMemory0() {
+    if (cachedUint8ArrayMemory0 === null || cachedUint8ArrayMemory0.byteLength === 0) {
+        cachedUint8ArrayMemory0 = new Uint8Array(wasm.memory.buffer);
+    }
+    return cachedUint8ArrayMemory0;
+}
+
+function getObject(idx) { return heap[idx]; }
+
+function handleError(f, args) {
+    try {
+        return f.apply(this, args);
+    } catch (e) {
+        wasm.__wbindgen_export3(addHeapObject(e));
+    }
+}
+
+let heap = new Array(1024).fill(undefined);
+heap.push(undefined, null, true, false);
+
+let heap_next = heap.length;
+
+function isLikeNone(x) {
+    return x === undefined || x === null;
+}
+
+function passArrayF32ToWasm0(arg, malloc) {
+    const ptr = malloc(arg.length * 4, 4) >>> 0;
+    getFloat32ArrayMemory0().set(arg, ptr / 4);
+    WASM_VECTOR_LEN = arg.length;
+    return ptr;
+}
+
+function passStringToWasm0(arg, malloc, realloc) {
+    if (realloc === undefined) {
+        const buf = cachedTextEncoder.encode(arg);
+        const ptr = malloc(buf.length, 1) >>> 0;
+        getUint8ArrayMemory0().subarray(ptr, ptr + buf.length).set(buf);
+        WASM_VECTOR_LEN = buf.length;
+        return ptr;
+    }
+
+    let len = arg.length;
+    let ptr = malloc(len, 1) >>> 0;
+
+    const mem = getUint8ArrayMemory0();
+
+    let offset = 0;
+
+    for (; offset < len; offset++) {
+        const code = arg.charCodeAt(offset);
+        if (code > 0x7F) break;
+        mem[ptr + offset] = code;
+    }
+    if (offset !== len) {
+        if (offset !== 0) {
+            arg = arg.slice(offset);
+        }
+        ptr = realloc(ptr, len, len = offset + arg.length * 3, 1) >>> 0;
+        const view = getUint8ArrayMemory0().subarray(ptr + offset, ptr + len);
+        const ret = cachedTextEncoder.encodeInto(arg, view);
+
+        offset += ret.written;
+        ptr = realloc(ptr, len, offset, 1) >>> 0;
+    }
+
+    WASM_VECTOR_LEN = offset;
+    return ptr;
+}
+
+function takeObject(idx) {
+    const ret = getObject(idx);
+    dropObject(idx);
+    return ret;
+}
+
+let cachedTextDecoder = new TextDecoder('utf-8', { ignoreBOM: true, fatal: true });
+cachedTextDecoder.decode();
+function decodeText(ptr, len) {
+    return cachedTextDecoder.decode(getUint8ArrayMemory0().subarray(ptr, ptr + len));
+}
+
+const cachedTextEncoder = new TextEncoder();
+
+if (!('encodeInto' in cachedTextEncoder)) {
+    cachedTextEncoder.encodeInto = function (arg, view) {
+        const buf = cachedTextEncoder.encode(arg);
+        view.set(buf);
+        return {
+            read: arg.length,
+            written: buf.length
+        };
+    };
+}
+
+let WASM_VECTOR_LEN = 0;
+
+const wasmPath = `${__dirname}/ruvector_attention_wasm_bg.wasm`;
+const wasmBytes = require('fs').readFileSync(wasmPath);
+const wasmModule = new WebAssembly.Module(wasmBytes);
+let wasm = new WebAssembly.Instance(wasmModule, __wbg_get_imports()).exports;
+wasm.__wbindgen_start();
diff --git a/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm_bg.wasm b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm_bg.wasm
new file mode 100644
index 00000000..8e23dfab
Binary files /dev/null and b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm_bg.wasm differ
diff --git a/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm_bg.wasm.d.ts b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm_bg.wasm.d.ts
new file mode 100644
index 00000000..7647f9ba
--- /dev/null
+++ b/crates/ruvector-attention-wasm/pkg/ruvector_attention_wasm_bg.wasm.d.ts
@@ -0,0 +1,71 @@
+/* tslint:disable */
+/* eslint-disable */
+export const memory: WebAssembly.Memory;
+export const __wbg_wasmadam_free: (a: number, b: number) => void;
+export const __wbg_wasmadamw_free: (a: number, b: number) => void;
+export const __wbg_wasmflashattention_free: (a: number, b: number) => void;
+export const __wbg_wasmhyperbolicattention_free: (a: number, b: number) => void;
+export const __wbg_wasminfonceloss_free: (a: number, b: number) => void;
+export const __wbg_wasmlinearattention_free: (a: number, b: number) => void;
+export const __wbg_wasmmoeattention_free: (a: number, b: number) => void;
+export const __wbg_wasmmultiheadattention_free: (a: number, b: number) => void;
+export const __wbg_wasmsgd_free: (a: number, b: number) => void;
+export const attention_weights: (a: number, b: number, c: number, d: number) => void;
+export const available_mechanisms: () => number;
+export const batch_normalize: (a: number, b: number, c: number) => void;
+export const cosine_similarity: (a: number, b: number, c: number, d: number, e: number) => void;
+export const l2_norm: (a: number, b: number) => number;
+export const log: (a: number, b: number) => void;
+export const log_error: (a: number, b: number) => void;
+export const normalize: (a: number, b: number, c: number, d: number) => void;
+export const pairwise_distances: (a: number, b: number) => void;
+export const random_orthogonal_matrix: (a: number, b: number) => void;
+export const scaled_dot_attention: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const softmax: (a: number, b: number, c: number) => void;
+export const version: (a: number) => void;
+export const wasmadam_learning_rate: (a: number) => number;
+export const wasmadam_new: (a: number, b: number) => number;
+export const wasmadam_reset: (a: number) => void;
+export const wasmadam_set_learning_rate: (a: number, b: number) => void;
+export const wasmadam_step: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmadamw_new: (a: number, b: number, c: number) => number;
+export const wasmadamw_reset: (a: number) => void;
+export const wasmadamw_step: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmadamw_weight_decay: (a: number) => number;
+export const wasmflashattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmflashattention_new: (a: number, b: number) => number;
+export const wasmhyperbolicattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmhyperbolicattention_curvature: (a: number) => number;
+export const wasmhyperbolicattention_new: (a: number, b: number) => number;
+export const wasminfonceloss_compute: (a: number, b: number, c: number, d: number, e: number, f: number, g: number) => void;
+export const wasminfonceloss_new: (a: number) => number;
+export const wasmlinearattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmlinearattention_new: (a: number, b: number) => number;
+export const wasmlocalglobalattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmlocalglobalattention_new: (a: number, b: number, c: number) => number;
+export const wasmlrscheduler_get_lr: (a: number) => number;
+export const wasmlrscheduler_new: (a: number, b: number, c: number) => number;
+export const wasmlrscheduler_reset: (a: number) => void;
+export const wasmlrscheduler_step: (a: number) => void;
+export const wasmmoeattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmmoeattention_new: (a: number, b: number, c: number) => number;
+export const wasmmultiheadattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmmultiheadattention_dim: (a: number) => number;
+export const wasmmultiheadattention_new: (a: number, b: number, c: number) => void;
+export const wasmmultiheadattention_num_heads: (a: number) => number;
+export const wasmsgd_learning_rate: (a: number) => number;
+export const wasmsgd_new: (a: number, b: number, c: number) => number;
+export const wasmsgd_reset: (a: number) => void;
+export const wasmsgd_set_learning_rate: (a: number, b: number) => void;
+export const wasmsgd_step: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const init: () => void;
+export const wasmadamw_set_learning_rate: (a: number, b: number) => void;
+export const wasmadamw_learning_rate: (a: number) => number;
+export const __wbg_wasmlocalglobalattention_free: (a: number, b: number) => void;
+export const __wbg_wasmlrscheduler_free: (a: number, b: number) => void;
+export const __wbindgen_export: (a: number, b: number) => number;
+export const __wbindgen_export2: (a: number, b: number, c: number, d: number) => number;
+export const __wbindgen_export3: (a: number) => void;
+export const __wbindgen_export4: (a: number, b: number, c: number) => void;
+export const __wbindgen_add_to_stack_pointer: (a: number) => number;
+export const __wbindgen_start: () => void;