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_08-28-10_69201a7f5283 /events.out.tfevents.1689582503.69201a7f5283
- Xet hash:
- ff12acea10f3ed57f97e100da24b0417aa3fa31d2ce9246f285d21e32f554ecc
- Size of remote file:
- 20.6 kB
- SHA256:
- 618b2df5c2ef9e2dfb1a995876b375d9a78e42bb9cc606e46b8acd2ecc3221ae
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