Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hebrew
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Shiry/whisper-large-v2-he with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shiry/whisper-large-v2-he with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Shiry/whisper-large-v2-he")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Shiry/whisper-large-v2-he") model = AutoModelForSpeechSeq2Seq.from_pretrained("Shiry/whisper-large-v2-he") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6a3580b501fb7e2c3e678b9bbedc1c169d16a36227e75d39e6d00d6f2da62ff
- Size of remote file:
- 6.17 GB
- SHA256:
- f3b5e3329b58537a1bddb55a4723d3f7c4f003faf8807cd565b88a9f816ba6e5
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