Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use MICADEE/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MICADEE/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="MICADEE/model")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("MICADEE/model") model = AutoModelForCTC.from_pretrained("MICADEE/model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbdbb5d0e1067a2ecbb99a19da9a9c246a6f359ed2240edbd735ef7eb930813b
- Size of remote file:
- 1.26 GB
- SHA256:
- 8ee2ae8470cbd3c613b196523cb1f0dbeaad660a9eb19a0eb035e2dc59815f03
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