Instructions to use bh4/whisper-ben with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bh4/whisper-ben with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bh4/whisper-ben")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bh4/whisper-ben") model = AutoModelForSpeechSeq2Seq.from_pretrained("bh4/whisper-ben", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (01078db9be7f8eec0881054fa4f4d061e56ee03e) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>dc10ae3
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Upload airkolkata180.wav
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Upload airkolkata60.wav
(audio file for testing)86029ba
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Upload tokenizer.json
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add files
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initial commit
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