Automatic Speech Recognition
Transformers
ONNX
Safetensors
English
multilingual
whisper
windyword
english
Instructions to use WindstormLabs/listen-windy-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/listen-windy-edge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="WindstormLabs/listen-windy-edge")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/listen-windy-edge", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,977 Bytes
8a4b8c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- whisper
- windyword
- english
- multilingual
library_name: transformers
pipeline_tag: automatic-speech-recognition
language:
- en
- multilingual
---
# WindyWord.ai STT — Windy Edge
**Multilingual speech-to-text engine. Transcribes audio in 100+ languages, with English as the primary trained domain.**
## Profile
- **Architecture:** 756M params · distil-whisper-large-v3
- **Profile:** edge / mobile
- **Base model:** [distil-whisper/distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3)
## Variants in this repo
| Subfolder | Format | Use case |
|---|---|---|
| `safetensors/` | PyTorch safetensors (FP32) | GPU inference (highest quality) |
| `ct2-int8/` | CTranslate2 INT8 | CPU inference (~25% size, 2-4× faster) |
| `onnx/` | ONNX FP32 | Cross-platform deployment |
| `onnx-int8/` | ONNX INT8 | Edge / mobile / WebAssembly |
## Usage
```python
from transformers import WhisperForConditionalGeneration, WhisperProcessor
processor = WhisperProcessor.from_pretrained("WindyWord/listen-windy-edge", subfolder="safetensors")
model = WhisperForConditionalGeneration.from_pretrained("WindyWord/listen-windy-edge", subfolder="safetensors")
```
For CPU inference via CTranslate2:
```python
import ctranslate2
# After downloading the ct2-int8 subfolder:
model = ctranslate2.models.Whisper("path/to/ct2-int8/")
```
## Commercial Use
Part of the [WindyWord.ai](https://windyword.ai) STT fleet. Visit windyword.ai for real-time voice-to-text + translation apps and API access.
---
## Provenance & License
Weights derived from [distil-whisper/distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3) under Apache-2.0 (inherited). Voice tiers are direct redistributions of the upstream community Whisper / distil-whisper variants; no LoRA fine-tuning has been applied to these voice models.
*Certified by Opus 4.6 Opus-Claw (Dr. C) on Veron-1 (RTX 5090, Mt Pleasant SC).*
|