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 /Jul13_17-46-10_c29dfb936ef1 /events.out.tfevents.1689270396.c29dfb936ef1.515594.0
- Xet hash:
- 16d55c2dd915fe1fca7926d5ca4f4cd8000586c3b4d240b4fd455b5188d493b4
- Size of remote file:
- 23.4 kB
- SHA256:
- 520bfed79e3a400c4256ea2313ca1c6c44d6eceff64b80031594a27e0e2490fd
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