Instructions to use sudoping01/karato-wav2vec2-nko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sudoping01/karato-wav2vec2-nko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sudoping01/karato-wav2vec2-nko")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("sudoping01/karato-wav2vec2-nko") model = AutoModelForCTC.from_pretrained("sudoping01/karato-wav2vec2-nko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sudoping01/karato-wav2vec2-nko: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/sudoping01/karato-wav2vec2-nko/resolve/main/training_args.bin
- Command line
-
hf download hf://sudoping01/karato-wav2vec2-nko/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sudoping01/karato-wav2vec2-nko/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- bd371d9b25fc1ada2ec835f6bf654f6347bedc132c4f2c08fba15135afed5fde
- Size of remote file:
- 5.2 kB
- SHA256:
- 63a18b3d7d911727941bed1038bbfc63b16822a35207b3273be85a028befb7c1
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