Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use cantillation/test42233 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cantillation/test42233 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cantillation/test42233")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cantillation/test42233") model = AutoModelForSpeechSeq2Seq.from_pretrained("cantillation/test42233", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 862950e7aea741e946ef1bf537d16a87ba556e8edf01a84fc7959a73238456fb
- Size of remote file:
- 5.24 kB
- SHA256:
- 2df0f27a1b8aad9d6c404020ebbf1e1deeb16f801a638a3403d7daf44c725a5d
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