Instructions to use cdli/whisper-small_finetuned_kenyan_swahili_nonstandard_speech_v0.9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cdli/whisper-small_finetuned_kenyan_swahili_nonstandard_speech_v0.9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cdli/whisper-small_finetuned_kenyan_swahili_nonstandard_speech_v0.9")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cdli/whisper-small_finetuned_kenyan_swahili_nonstandard_speech_v0.9") model = AutoModelForSpeechSeq2Seq.from_pretrained("cdli/whisper-small_finetuned_kenyan_swahili_nonstandard_speech_v0.9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fb15ef3559f411bee667c476a9e67e6551c7353e82e293ad595f34b83c687bc
- Size of remote file:
- 5.97 kB
- SHA256:
- fb2e683ee8a76625e9115182e262865957195fe6ecaa4bd11335c254f97e9dea
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