David Snelling
563b983fcc
- 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.
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1,018 B
JSON
52 lines
No EOL
1,018 B
JSON
{
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"format": "graph-model",
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"generatedBy": "TensorFlow.js v4.22.0",
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"convertedBy": "Brainy download-model script",
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"modelTopology": {
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"class_name": "GraphModel",
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"config": {
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"name": "universal-sentence-encoder"
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}
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},
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"userDefinedMetadata": {
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"signature": {
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"inputs": {
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"inputs": {
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"name": "inputs",
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"dtype": "string",
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"shape": [
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-1
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]
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}
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},
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"outputs": {
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"outputs": {
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"name": "outputs",
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"dtype": "float32",
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"shape": [
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-1,
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512
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]
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}
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}
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}
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},
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"weightsManifest": [
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{
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"paths": [
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"group1-shard1of1.bin"
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],
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"weights": [
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{
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"name": "embedding_matrix",
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"shape": [
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512,
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512
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],
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"dtype": "float32"
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}
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]
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}
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],
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"modelUrl": "https://tfhub.dev/tensorflow/tfjs-model/universal-sentence-encoder/1/default/1"
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} |