Instructions to use q-henric/kb-whisper-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use q-henric/kb-whisper-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="q-henric/kb-whisper-large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("q-henric/kb-whisper-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("q-henric/kb-whisper-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add onnx/encoder_model_uint8.onnx
Browse files
onnx/encoder_model_uint8.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:855f661f0d7aedf504b038a5298d0821a9c93c508785455f9a861ea23bca80e9
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size 644795347
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