Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use OmBenz/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OmBenz/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="OmBenz/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("OmBenz/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("OmBenz/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a3a0ce26ccbd2d9796a6f2fa7f7b64b1637170356f29cd1ff65651155c50cfa
- Size of remote file:
- 4.86 kB
- SHA256:
- d573e395d8bdbfa3cafff1f08ac50178399f636de37233c5182e9a6a6fa4c2aa
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