Instructions to use joshuarwanda/wav2vec2-large-xls-r-300m-swahili-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joshuarwanda/wav2vec2-large-xls-r-300m-swahili-colab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="joshuarwanda/wav2vec2-large-xls-r-300m-swahili-colab")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("joshuarwanda/wav2vec2-large-xls-r-300m-swahili-colab") model = AutoModelForCTC.from_pretrained("joshuarwanda/wav2vec2-large-xls-r-300m-swahili-colab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 594f7f8fa73df48fd39bd43d4e3eac26224bc422ccb85a1e15654cc3fa779229
- Size of remote file:
- 4.6 kB
- SHA256:
- 8e0fa8c9dcb188e1f705e1e456521f1fa9a50ffd3831bfb9b7f4cca1f463bf4f
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