Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use mcamara/whisper-tiny-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcamara/whisper-tiny-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mcamara/whisper-tiny-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mcamara/whisper-tiny-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("mcamara/whisper-tiny-dv") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files
runs/Jul24_18-31-57_byo-WS2/events.out.tfevents.1690216387.byo-WS2
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training_args.bin
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