brainy/models/sentence-encoder/model.json

52 lines
1,018 B
JSON
Raw Normal View History

**feat(models): add scripts for model compression, bundling, and optimization** - Added new scripts under `brainy-models-package/scripts`: - **`compress-models.js`**: Implements model compression with float16 and int8 precision to create optimized variants of Universal Sentence Encoder models. - **`download-full-models.js`**: Downloads the complete Universal Sentence Encoder model for offline usage. - **`download-model.js`**: Downloads reference files for TensorFlow Hub-based Universal Sentence Encoder. - Introduced a demonstration script: - **`demo-optional-model-bundling.js`**: Highlights the solution of bundling models to eliminate network dependency, ensuring reliability and offline capability. - Key Features: - **Compression**: - Reduced model size with float16 (balanced precision and size) and int8 (low-memory environments) options. - Generated compression summaries for quick insights into model variants and saved space. - **Offline Reliability**: - Bundled versions eliminate first-load delays, network dependencies, and failures. - Ensures rapid initialization in offline and memory-constrained scenarios. - **Dynamic Optimization**: - Tailored optimization profiles for various use cases: general, low-memory, and high-performance. - **Demonstration and Documentation**: - Comprehensive demo showcasing benefits of bundled models over online loading. - Examples for usage, testing, and integration with Brainy. **Purpose**: Introduce essential scripts and tools to enable efficient, offline-ready model usage, streamlining the embedding workflow while ensuring reliability in production and resource-constrained environments.
2025-08-01 15:35:08 -07:00
{
"format": "graph-model",
"generatedBy": "TensorFlow.js v4.22.0",
"convertedBy": "Brainy download-model script",
"modelTopology": {
"class_name": "GraphModel",
"config": {
"name": "universal-sentence-encoder"
}
},
"userDefinedMetadata": {
"signature": {
"inputs": {
"inputs": {
"name": "inputs",
"dtype": "string",
"shape": [
-1
]
}
},
"outputs": {
"outputs": {
"name": "outputs",
"dtype": "float32",
"shape": [
-1,
512
]
}
}
}
},
"weightsManifest": [
{
"paths": [
"group1-shard1of1.bin"
],
"weights": [
{
"name": "embedding_matrix",
"shape": [
512,
512
],
"dtype": "float32"
}
]
}
],
"modelUrl": "https://tfhub.dev/tensorflow/tfjs-model/universal-sentence-encoder/1/default/1"
}