67 lines
1.8 KiB
JSON
67 lines
1.8 KiB
JSON
{
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"name": "@ruvector/attention-wasm",
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"version": "0.1.32",
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"description": "High-performance WebAssembly attention mechanisms for transformers and LLMs: Multi-Head, Flash Attention, Hyperbolic, Linear (Performer), MoE, Local-Global, and CGT Sheaf Attention with coherence gating. GPU-accelerated with SIMD fallback.",
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"main": "pkg/ruvector_attention_wasm.js",
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"module": "pkg/ruvector_attention_wasm.js",
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"types": "pkg/ruvector_attention_wasm.d.ts",
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"files": [
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"pkg/",
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"js/",
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"README.md"
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],
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"scripts": {
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"build": "wasm-pack build --target web --out-dir pkg",
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"build:node": "wasm-pack build --target nodejs --out-dir pkg-node",
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"build:bundler": "wasm-pack build --target bundler --out-dir pkg-bundler",
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"build:all": "npm run build && npm run build:node && npm run build:bundler",
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"test": "wasm-pack test --headless --firefox",
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"test:chrome": "wasm-pack test --headless --chrome",
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"clean": "rm -rf pkg pkg-node pkg-bundler target",
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"prepublishOnly": "npm run build"
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},
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"repository": {
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"type": "git",
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"url": "git+https://github.com/ruvnet/ruvector.git"
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},
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"keywords": [
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"wasm",
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"webassembly",
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"attention",
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"transformer",
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"llm",
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"machine-learning",
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"neural-networks",
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"multi-head-attention",
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"flash-attention",
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"hyperbolic",
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"moe",
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"mixture-of-experts",
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"coherence",
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"cgt",
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"sheaf-attention",
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"ai",
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"deep-learning",
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"gpu",
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"simd",
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"infonce",
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"contrastive-learning"
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],
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"author": "rUv <team@ruvector.dev>",
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"license": "MIT OR Apache-2.0",
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"bugs": {
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"url": "https://github.com/ruvnet/ruvector/issues"
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},
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"homepage": "https://ruv.io/ruvector",
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"devDependencies": {
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"@types/node": "^20.0.0",
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"typescript": "^5.0.0"
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},
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"engines": {
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"node": ">=16.0.0"
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},
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"publishConfig": {
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"access": "public"
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}
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}
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