Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Mongolian
wav2vec2-bert
Generated from Trainer
Instructions to use Cafet/w2v-bert-version-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cafet/w2v-bert-version-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Cafet/w2v-bert-version-final")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Cafet/w2v-bert-version-final") model = AutoModelForCTC.from_pretrained("Cafet/w2v-bert-version-final") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cebf542ae944c83dc74e9ac2c030c8495b6ff8e6c267f3c1130776c0a1e488f6
- Size of remote file:
- 4.98 kB
- SHA256:
- a8590a3c1c4c6e68d552e48a520b143bf6b7e17e319754768e3781bcb3c6412f
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