Instructions to use cdli/whisper-tiny_finetuned_kenyan_english_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-tiny_finetuned_kenyan_english_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-tiny_finetuned_kenyan_english_nonstandard_speech_v0.9")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cdli/whisper-tiny_finetuned_kenyan_english_nonstandard_speech_v0.9") model = AutoModelForSpeechSeq2Seq.from_pretrained("cdli/whisper-tiny_finetuned_kenyan_english_nonstandard_speech_v0.9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c219b330425f91995c4d9df5ecc028753930fc2f55cb6d6a5bbf802eef9a5108
- Size of remote file:
- 151 MB
- SHA256:
- ede66594af90527294ff4b0bca1d65082f11f25428526868563df2fe58208878
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