Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use OverloadedOperator/tokomni-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OverloadedOperator/tokomni-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="OverloadedOperator/tokomni-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("OverloadedOperator/tokomni-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("OverloadedOperator/tokomni-whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 528c5274838e5fc6685219a7a51e81e850df62b8ca49eaff39f1df054fef1263
- Size of remote file:
- 5.11 kB
- SHA256:
- c8d1081fe810d15e2f968c8b851136242a46ab4d75c40ec09f8a7d12caddb2d6
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