Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use hackvermin/whisper-tiny-us with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hackvermin/whisper-tiny-us with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hackvermin/whisper-tiny-us")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hackvermin/whisper-tiny-us") model = AutoModelForSpeechSeq2Seq.from_pretrained("hackvermin/whisper-tiny-us") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20854b3b7ad2001483821c24ba13817c668850e94ad42966451a828203bc684d
- Size of remote file:
- 151 MB
- SHA256:
- b78016f346d880c85fd2d01536937ee899bd3bcd0d9c93313797b21f0bf63bdf
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