Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Yoruba
wav2vec2-bert
Generated from Trainer
Eval Results (legacy)
Instructions to use oyemade/w2v-bert-2.0-yoruba-CV17.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oyemade/w2v-bert-2.0-yoruba-CV17.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oyemade/w2v-bert-2.0-yoruba-CV17.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("oyemade/w2v-bert-2.0-yoruba-CV17.0") model = AutoModelForCTC.from_pretrained("oyemade/w2v-bert-2.0-yoruba-CV17.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from oyemade/w2v-bert-2.0-yoruba-CV17.0: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/oyemade/w2v-bert-2.0-yoruba-CV17.0/resolve/main/training_args.bin
- Command line
-
hf download hf://oyemade/w2v-bert-2.0-yoruba-CV17.0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/oyemade/w2v-bert-2.0-yoruba-CV17.0/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 565b16cfb2fcc85b7a6079423d15a3ff790ebf21bba081a8f33dae1246a80e62
- Size of remote file:
- 5.11 kB
- SHA256:
- 52297555677ec823c5754ba7f2de6d2157118c44ac81094419a8b2b7a474c701
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