Instructions to use WindyWord/listen-windy-lingua-zh-ct2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/listen-windy-lingua-zh-ct2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="WindyWord/listen-windy-lingua-zh-ct2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/listen-windy-lingua-zh-ct2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
tags:
- automatic-speech-recognition
- whisper
- windyword
- chinese
- zh
library_name: transformers
pipeline_tag: automatic-speech-recognition
language:
- zh
---
# WindyWord.ai STT — Chinese (Mandarin) Lingua (CPU INT8 (CTranslate2))
**Transcribes Chinese (Mandarin) speech (Sino-Tibetan > Sinitic).**
## Quality
- **WER:** unverified by WindyWord harness yet. Imported from upstream community fine-tune.
## About this variant
This is the **ct2-int8** deployment format of our Chinese (Mandarin) Lingua STT model. Load it via the `ct2-int8/` subfolder.
Part of the [WindyWord.ai](https://windyword.ai) STT fleet — covering 35+ languages that commercial speech-to-text APIs underserve, with proper dialect / script disclosures where they matter.
## Usage
```python
from transformers import WhisperForConditionalGeneration, WhisperProcessor
processor = WhisperProcessor.from_pretrained("WindyWord/listen-windy-lingua-zh-ct2", subfolder="ct2-int8")
model = WhisperForConditionalGeneration.from_pretrained("WindyWord/listen-windy-lingua-zh-ct2", subfolder="ct2-int8")
```
## Commercial Use
Visit [windyword.ai](https://windyword.ai) for apps and API access.
---
## Provenance & License
Weights derived from upstream community Whisper fine-tunes (see individual model card for exact lineage). Redistributed under Apache-2.0 (inherited).
*Certified by Opus 4.6 Opus-Claw (Dr. C) on Veron-1 (RTX 5090, Mt Pleasant SC).*
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