Instructions to use Alwaly/whisper-medium-wolof with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alwaly/whisper-medium-wolof with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Alwaly/whisper-medium-wolof")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Alwaly/whisper-medium-wolof") model = AutoModelForSpeechSeq2Seq.from_pretrained("Alwaly/whisper-medium-wolof", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Alwaly/whisper-medium-wolof: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Alwaly/whisper-medium-wolof/resolve/main/training_args.bin
- Command line
-
hf download hf://Alwaly/whisper-medium-wolof/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Alwaly/whisper-medium-wolof/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- f85375e3d6b1f72af82702f649f7b73b072bc9ea4db996c418688d702e6d6d88
- Size of remote file:
- 5.37 kB
- SHA256:
- 5bb6168341491e58fbf10c198e618137ea66d6097165941ebaa38a93f2740fe9
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