Automatic Speech Recognition
ONNX
Transformers.js
onnxruntime
onnxruntime-web
asr
speech-recognition
robust-asr
quantized
int4
int8
matmulnbits
gptq
on-device
browser
web
qwen3
qwen3-asr
mega-asr
Instructions to use VidraAI/mega-asr-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use VidraAI/mega-asr-onnx with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'VidraAI/mega-asr-onnx');
Download preprocessor_config.json from VidraAI/mega-asr-onnx: direct link, hf CLI and curl.
- Browser
- Download file 330 Bytes
-
https://huggingface.co/VidraAI/mega-asr-onnx/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://VidraAI/mega-asr-onnx/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/VidraAI/mega-asr-onnx/resolve/main/preprocessor_config.json
330 Bytes
| { | |
| "chunk_length": 30, | |
| "dither": 0.0, | |
| "feature_extractor_type": "WhisperFeatureExtractor", | |
| "feature_size": 128, | |
| "hop_length": 160, | |
| "n_fft": 400, | |
| "n_samples": 480000, | |
| "nb_max_frames": 3000, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "Qwen3ASRProcessor", | |
| "return_attention_mask": true | |
| } |