Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Belarusian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use ales/whisper-tiny-be-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ales/whisper-tiny-be-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ales/whisper-tiny-be-test")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ales/whisper-tiny-be-test") model = AutoModelForSpeechSeq2Seq.from_pretrained("ales/whisper-tiny-be-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 200
Browse files
pytorch_model.bin
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runs/Dec13_11-33-05_d7f040c448a8/events.out.tfevents.1670931197.d7f040c448a8.8569.0
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train.log
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{'loss': 0.2765, 'learning_rate': 9.050000000000001e-06, 'epoch': 0.1}
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{'loss': 0.2765, 'learning_rate': 9.050000000000001e-06, 'epoch': 0.1}
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