Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use eai6/whisper-tiny-exp.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eai6/whisper-tiny-exp.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eai6/whisper-tiny-exp.en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("eai6/whisper-tiny-exp.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("eai6/whisper-tiny-exp.en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47266d6017dd13bcb5fd66d9a62b0d927e4b4aa2cffc4c11a7395875e0163461
- Size of remote file:
- 5.05 kB
- SHA256:
- 78468db03b15ab60e4c4ef1a05bd0c376db7b1113b09cba43d8db4f1ec9a9595
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