Instructions to use sjenit/embeddinggemma-2-ONNX-wasm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use sjenit/embeddinggemma-2-ONNX-wasm with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'sjenit/embeddinggemma-2-ONNX-wasm');
Download preprocessor_config.json from sjenit/embeddinggemma-2-ONNX-wasm: direct link, hf CLI and curl.
- Browser
- Download file 560 Bytes
-
https://huggingface.co/sjenit/embeddinggemma-2-ONNX-wasm/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://sjenit/embeddinggemma-2-ONNX-wasm/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/sjenit/embeddinggemma-2-ONNX-wasm/resolve/main/preprocessor_config.json
560 Bytes
| { | |
| "dither": 0.0, | |
| "feature_extractor_type": "Gemma4AudioFeatureExtractor", | |
| "feature_size": 128, | |
| "fft_length": 512, | |
| "fft_overdrive": false, | |
| "frame_length": 320, | |
| "hop_length": 160, | |
| "input_scale_factor": 1.0, | |
| "max_frequency": 8000.0, | |
| "mel_floor": 0.001, | |
| "min_frequency": 0.0, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "per_bin_mean": null, | |
| "per_bin_stddev": null, | |
| "preemphasis": 0.0, | |
| "preemphasis_htk_flavor": true, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "processor_class": "EmbeddingGemma2Processor" | |
| } | |