Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Ellight/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ellight/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Ellight/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Ellight/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("Ellight/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2bcccddd49509e375326f1f665809b0d623b5a7941b9209a7930fd38ddae7a3
- Size of remote file:
- 5.18 kB
- SHA256:
- b072f13b37d270392e974ea2c09a640f313f901cd5967b8f4ad20d38dc54e613
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