Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use misiker/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use misiker/trainer_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="misiker/trainer_output")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("misiker/trainer_output") model = AutoModelForCTC.from_pretrained("misiker/trainer_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a2ba122d6b203bd8b0755ee4fc23350096e597d632e566369ab28c436f2e7d0
- Size of remote file:
- 5.65 kB
- SHA256:
- 229e63f6df332a3c79d7ba7cb2088c30bef41335c7037c60fffde2008d3aaf78
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