Buckets:
1.87 GB
45 files
Updated about 1 month ago
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| Name | Size | Uploaded | Xet hash |
|---|---|---|---|
| onnx | 31 items | ||
| .gitattributes | 1.48 kB xet | b4195e66 | |
| README.md | 3.21 kB xet | 1058abde | |
| added_tokens.json | 2.08 kB xet | 645efe18 | |
| config.json | 2.2 kB xet | 36237bca | |
| generation_config.json | 1.59 kB xet | 54cf668f | |
| merges.txt | 456 kB xet | 7b59996a | |
| normalizer.json | 52.7 kB xet | 1301c121 | |
| preprocessor_config.json | 339 Bytes xet | 78385b61 | |
| quant_config.json | 2.84 kB xet | 4ead79a0 | |
| quantize_config.json | 2.84 kB xet | d004f3b5 | |
| special_tokens_map.json | 1.72 kB xet | 37c294c0 | |
| tokenizer.json | 2.13 MB xet | 4b7b973a | |
| tokenizer_config.json | 835 Bytes xet | 61d9ad9a | |
| vocab.json | 999 kB xet | 66ea8330 |
Whisper
openai/whisper-tiny.en with ONNX weights to be compatible with Transformers.js.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Transcribe English.
import { pipeline } from '@huggingface/transformers';
// Create speech recognition pipeline
const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en');
// Transcribe audio from URL
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
const output = await transcriber(url);
// { text: " And so my fellow Americans ask not what your country can do for you, ask what you can do for your country." }
Example: Transcribe English w/ timestamps.
import { pipeline } from '@huggingface/transformers';
// Create speech recognition pipeline
const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en');
// Transcribe audio from URL with timestamps
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
const output = await transcriber(url, { return_timestamps: true });
// {
// text: " And so my fellow Americans ask not what your country can do for you, ask what you can do for your country."
// chunks: [
// { timestamp: [0, 8], text: " And so my fellow Americans ask not what your country can do for you" }
// { timestamp: [8, 11], text: " ask what you can do for your country." }
// ]
// }
Example: Transcribe English w/ word-level timestamps.
import { pipeline } from '@huggingface/transformers';
// Create speech recognition pipeline
const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en');
// Transcribe audio from URL with word-level timestamps
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
const output = await transcriber(url, { return_timestamps: 'word' });
// {
// "text": " And so my fellow Americans ask not what your country can do for you ask what you can do for your country.",
// "chunks": [
// { "text": " And", "timestamp": [0, 0.78] },
// { "text": " so", "timestamp": [0.78, 1.06] },
// { "text": " my", "timestamp": [1.06, 1.46] },
// ...
// { "text": " for", "timestamp": [9.72, 9.92] },
// { "text": " your", "timestamp": [9.92, 10.22] },
// { "text": " country.", "timestamp": [10.22, 13.5] }
// ]
// }
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).
- Total size
- 1.87 GB
- Files
- 45
- Last updated
- Sep 14
- Pre-warmed CDN
- US EU US EU