Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use taohoang/whisper-tiny-en-US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taohoang/whisper-tiny-en-US with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="taohoang/whisper-tiny-en-US")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("taohoang/whisper-tiny-en-US") model = AutoModelForSpeechSeq2Seq.from_pretrained("taohoang/whisper-tiny-en-US", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 70
Browse files
pytorch_model.bin
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runs/Aug05_12-26-20_1c0dc86d8d2b/events.out.tfevents.1691238391.1c0dc86d8d2b.19117.0
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