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
Refresh README — uniform WindyWord template with WER tier + dialect notes
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README.md
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- automatic-speech-recognition
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library_name: transformers
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pipeline_tag: automatic-speech-recognition
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# WindyWord.ai STT —
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**Transcribes
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## Quality
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## About this variant
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This is the **ct2-int8** deployment format of our
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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.
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- chinese
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library_name: transformers
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pipeline_tag: automatic-speech-recognition
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---
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# WindyWord.ai STT — Chinese (Mandarin) Lingua (CPU INT8 (CTranslate2))
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**Transcribes Chinese (Mandarin) speech (Sino-Tibetan > Sinitic).**
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## Quality
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## About this variant
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This is the **ct2-int8** deployment format of our Chinese (Mandarin) Lingua STT model. Load it via the `ct2-int8/` subfolder.
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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.
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