Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use cantillation/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cantillation/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cantillation/test2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cantillation/test2") model = AutoModelForSpeechSeq2Seq.from_pretrained("cantillation/test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00b804ea128f794ad94fc67c88a21359a0436cc91777fddc592ab429498677e0
- Size of remote file:
- 151 MB
- SHA256:
- f1bd0322c8c0faa06dede9c2c61b7562510ecf20ae51d80ae2add48b807f45cd
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