Instructions to use tooape/embeddinggemma-300m-qat-q8-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use tooape/embeddinggemma-300m-qat-q8-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'tooape/embeddinggemma-300m-qat-q8-ONNX');
EmbeddingGemma-300m β 64K-vocab-trimmed, PTQ-q4 (transformers.js)
Vocabulary-trimmed (262K β 64K EN+code ByteLevel-BPE) EmbeddingGemma-300m, PTQ
int4, exported as a single self-contained onnx/model_q4.onnx (external data
inlined β required for iOS WKWebView). Built for the Obsidian "Seek" plugin.
NOTE: the repo slug still says qat-q8 for URL stability β this is a misnomer;
the actual model is trimmed PTQ-q4 (no QAT, not q8).
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Model tree for tooape/embeddinggemma-300m-qat-q8-ONNX
Base model
google/embeddinggemma-300m