Instructions to use Eyesiga/Runyakore_XlSR_WAV2VEC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eyesiga/Runyakore_XlSR_WAV2VEC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Eyesiga/Runyakore_XlSR_WAV2VEC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Eyesiga/Runyakore_XlSR_WAV2VEC") model = AutoModelForCTC.from_pretrained("Eyesiga/Runyakore_XlSR_WAV2VEC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Eyesiga/Runyakore_XlSR_WAV2VEC: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Eyesiga/Runyakore_XlSR_WAV2VEC/resolve/main/training_args.bin
- Command line
-
hf download hf://Eyesiga/Runyakore_XlSR_WAV2VEC/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Eyesiga/Runyakore_XlSR_WAV2VEC/resolve/main/training_args.bin
4.73 kB
- Size of remote file:
- 4.73 kB
- SHA256:
- 434638faa0ffe1920bcd669ba76f11609f5edcd846abc5320fe1c620e31a6862
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