dpshade22/embeddinggemma-scripture-v1-onnx

EmbeddingGemma-300M Fine-tuned for Biblical Text Search (ONNX)

This is the ONNX version of our fine-tuned EmbeddingGemma-300M model specialized for biblical text search and retrieval. This version is optimized for web deployment using transformers.js.

Model Performance

• —Accuracy@1: 12.00% (13x improvement over base model)
• —Accuracy@3: 15.00%
• —Accuracy@10: 31.00%
• —Training Steps: 25 (optimal stopping point)
• —Base Model Accuracy@1: 0.91%

Usage with Transformers.js

import { AutoTokenizer, AutoModel } from '@huggingface/transformers';

// Load the model
const model = await AutoModel.from_pretrained('dpshade22/embeddinggemma-scripture-v1-onnx');
const tokenizer = await AutoTokenizer.from_pretrained('dpshade22/embeddinggemma-scripture-v1-onnx');

// Encode queries (use search_query: prefix)
const query = "search_query: What is love?";
const query_embedding = await model.encode([query]);

// Encode documents (use search_document: prefix)  
const document = "search_document: Love is patient and kind";
const doc_embedding = await model.encode([document]);

Prefixes

For optimal performance, use these prefixes:

• —Queries: "search_query: your question here"
• —Documents: "search_document: scripture text here"

Model Details

• —Base Model: google/embeddinggemma-300m
• —Training Data: 26,276 biblical text pairs
• —Training Steps: 25 steps (optimal stopping point)
• —Learning Rate: 2.0e-04
• —Batch Size: 8
• —Output Dimensions: 768D (supports Matryoshka 384D, 128D)
• —ONNX Conversion: Using nixiesearch/onnx-convert specialized tool

Training Details

• —Training Data: 26,276 biblical text pairs
• —Learning Rate: 2.0e-04
• —Batch Size: 8
• —Training Strategy: Early stopping at 25 steps to prevent overfitting
• —Output Dimensions: 768D (supports Matryoshka 384D, 128D)

Intended Use

This model is designed for:

• —Biblical text search and retrieval in web applications
• —Finding relevant scripture passages
• —Semantic similarity of religious texts
• —Question answering on biblical topics
• —Offline PWA applications using transformers.js

Conversion Details

• —Converted using: nixiesearch/onnx-convert specialized tool
• —ONNX Opset: 17
• —Optimization Level: 1
• —Max difference from original: 1.9e-05 (within acceptable tolerance)

Related Models

• —Original PyTorch version: dpshade22/embeddinggemma-scripture-v1
• —Base model: google/embeddinggemma-300m
• —Reference ONNX: onnx-community/embeddinggemma-300m-ONNX