Automatic Speech Recognition
Transformers
Safetensors
Ikposo
whisper
african-languages
waxal
waxalnet
Instructions to use waxal-benchmarking/whisper-small-waxal-kpo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use waxal-benchmarking/whisper-small-waxal-kpo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="waxal-benchmarking/whisper-small-waxal-kpo")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("waxal-benchmarking/whisper-small-waxal-kpo") model = AutoModelForSpeechSeq2Seq.from_pretrained("waxal-benchmarking/whisper-small-waxal-kpo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
c489d33 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b633f5992ca17c47063a6f981b1b73fa301c4ca93a57a013b032a007760d5f0b
size 5393
|