Transformers
PyTorch
Amharic
Swahili
Wolof
wav2vec2
pretraining
speech pretraining
african
fongbe
swahili
wolof
ahmaric
Instructions to use OctaSpace/wav2vec2-large-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OctaSpace/wav2vec2-large-finetuned with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("OctaSpace/wav2vec2-large-finetuned") model = AutoModelForPreTraining.from_pretrained("OctaSpace/wav2vec2-large-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f0f26c2c88ec6a1cce0e7c2551d975144d24f60a05ab44bf37497bfadd794b4
- Size of remote file:
- 1.27 GB
- SHA256:
- 307879c691d7d2964d7c0ba410c58e13e82ef9ed63d60b086ac0cbce47b832d8
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