| --- |
| library_name: transformers.js |
| pipeline_tag: automatic-speech-recognition |
| license: apache-2.0 |
| base_model: primeline/distil-whisper-large-v3-german |
| tags: |
| - transformers.js |
| - onnx |
| - whisper |
| - speech |
| - automatic-speech-recognition |
| - timestamps |
| --- |
| |
| # distil-whisper-large-v3-german_timestamped-ONNX |
| |
| This repository contains ONNX weights for [`primeline/distil-whisper-large-v3-german`](https://huggingface.co/primeline/distil-whisper-large-v3-german) |
| prepared for use with Transformers.js. |
| |
| Timestamp support is preserved through the exported Whisper generation config. |
| Available dtypes in this export: `fp32, fp16, q4, q8`. |
| |
| The repository layout follows the standard Transformers.js Whisper convention: |
| |
| - processor, tokenizer, and config files in the repository root |
| - encoder and merged decoder ONNX files inside `onnx/` |
| |
| ## Usage (Transformers.js) |
| |
| ```js |
| import { pipeline } from "@huggingface/transformers"; |
| |
| const transcriber = await pipeline("automatic-speech-recognition", "<your-hf-username>/distil-whisper-large-v3-german_timestamped-ONNX", { |
| device: "webgpu", |
| dtype: "fp16", // or "fp32", "q4", "q8" |
| }); |
|
|
| const output = await transcriber("audio.mp3", { |
| chunk_length_s: 30, |
| return_timestamps: "word", |
| }); |
| |
| console.log(output.text); |
| console.log(output.chunks?.slice(0, 3)); |
| ``` |
| |
| Recommended choices: |
| |
| - `fp32`: highest precision, typically for server-side or high-memory WebGPU |
| - `fp16`: smaller WebGPU model with good speed/quality tradeoff |
| - `q8`: smaller CPU/WASM model |
| - `q4`: smallest model, best for constrained devices |
| |
| ## Source Model |
| |
| - Base model: [`primeline/distil-whisper-large-v3-german`](https://huggingface.co/primeline/distil-whisper-large-v3-german) |
| - Export format: ONNX |
| - Intended runtime: [Transformers.js](https://huggingface.co/docs/transformers.js) |
| |
