Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use cantillation/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cantillation/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cantillation/test")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cantillation/test") model = AutoModelForSpeechSeq2Seq.from_pretrained("cantillation/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ca443c5700bdd311f7e4528d31179fb54666a903f26af54d1859be40cd2df7b
- Size of remote file:
- 5.24 kB
- SHA256:
- 8ca3fb93fe2ed654f226451107690437001f23942a9bbe18e4566bfce9289ad6
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