Automatic Speech Recognition
Transformers
Safetensors
English
whisper
african-accented-english
clinical-asr
afrispeech
Eval Results (legacy)
Instructions to use Professor/whisper-small-afrispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Professor/whisper-small-afrispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Professor/whisper-small-afrispeech")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Professor/whisper-small-afrispeech") model = AutoModelForSpeechSeq2Seq.from_pretrained("Professor/whisper-small-afrispeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b430321fb54065a98fc2cc2ace485f76f57e2d3e03e0164cd947537c34f2f4f
- Size of remote file:
- 5.39 kB
- SHA256:
- 9706bd0d1f832f80ab21c344dbaa5e1571bf7486d7c0153c79980dff531c6107
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