Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sandiago21/whisper-large-v2-greek with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandiago21/whisper-large-v2-greek with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sandiago21/whisper-large-v2-greek")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sandiago21/whisper-large-v2-greek") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sandiago21/whisper-large-v2-greek", device_map="auto") - Notebooks
- Google Colab
- Kaggle
whisper-large-v2-greek / runs /Jul17_08-18-24_69201a7f5283 /events.out.tfevents.1689581913.69201a7f5283
- Xet hash:
- 421087086a72818798ef55ad1418f95728e6b60ee853625453ff914e4df65cb5
- Size of remote file:
- 5.77 kB
- SHA256:
- fdb0ee990665e6f544f2dbc367396944ec87141ceeba3aedbd2b3c7c71f98ab4
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