Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Daniel981215/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Daniel981215/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Daniel981215/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Daniel981215/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("Daniel981215/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33f6b6a2ccaa69920ab6c13577f4dcb9fb8a428677ab144d77c765b01cdbb8df
- Size of remote file:
- 151 MB
- SHA256:
- 8b44380f6c24d14b570cca033b6d41991a537705897f9aa126bd7a022f34e08d
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