ruvector-attention-wasm 2.1.0

High-performance WebAssembly attention mechanisms: Multi-Head, Flash, Hyperbolic, MoE, CGT Sheaf Attention with GPU acceleration for transformers and LLMs
Documentation 
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{
  "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"
  ]
}