Automatic Speech Recognition
Transformers
ONNX
Safetensors
English
multilingual
whisper
windyword
english
Instructions to use WindyWord/listen-windy-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/listen-windy-lite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="WindyWord/listen-windy-lite")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/listen-windy-lite", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Refresh README — uniform WindyWord template with WER tier + dialect notes
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## Provenance & License
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Weights derived from [openai/whisper-base](https://huggingface.co/openai/whisper-base) under Apache-2.0 (inherited).
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*Certified by Opus 4.6 Opus-Claw (Dr. C) on Veron-1 (RTX 5090, Mt Pleasant SC).*
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## Provenance & License
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Weights derived from [openai/whisper-base](https://huggingface.co/openai/whisper-base) 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.
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*Certified by Opus 4.6 Opus-Claw (Dr. C) on Veron-1 (RTX 5090, Mt Pleasant SC).*
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