Instructions to use ak3ra/wav2vec2-base-runyankole with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ak3ra/wav2vec2-base-runyankole with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ak3ra/wav2vec2-base-runyankole")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ak3ra/wav2vec2-base-runyankole") model = AutoModelForCTC.from_pretrained("ak3ra/wav2vec2-base-runyankole", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ak3ra/wav2vec2-base-runyankole: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/ak3ra/wav2vec2-base-runyankole/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ak3ra/wav2vec2-base-runyankole/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ak3ra/wav2vec2-base-runyankole/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 17ff1fa15c8feafa56783f4979a5dcfec9a5aad6188095730cedd88f2de5cfd8
- Size of remote file:
- 378 MB
- SHA256:
- 7faf987e7800c96b7735676f0b750e91a3c64807ecb2d52d7a074b85dd0c5ce9
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