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:
- 3d6cac3032f16cace44386421c2f8b12006ef51e5d0c9f8b5d126ba42dc77f67
- Size of remote file:
- 298 MB
- SHA256:
- 03680f491f461ea19f44df6b06d201c150df59ebd8a23566c1ce2aec4e97c9c8
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