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 /Jul15_23-20-27_69201a7f5283 /1689463370.6572888 /events.out.tfevents.1689463370.69201a7f5283
- Xet hash:
- a3d37f4fbd83722b4cc6cc3e4e54532cb01adb1ff6d71c53bea25e2b7408fdb2
- Size of remote file:
- 5.91 kB
- SHA256:
- a22249babbcfb2ae755447c4494d226635595341fd6a419d266ed492534bf03f
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