Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Greek
whisper
hf-asr-leaderboard
whisper-medium
mozilla-foundation/common_voice_11_0
greek
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use emilios/whisper-medium-el with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilios/whisper-medium-el with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emilios/whisper-medium-el")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("emilios/whisper-medium-el") model = AutoModelForSpeechSeq2Seq.from_pretrained("emilios/whisper-medium-el", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca7a1d248d9a4849709ab7365a52baa80f8c6f3da6a4d4a7c0a694ce8ce9d10c
- Size of remote file:
- 3.06 GB
- SHA256:
- 2ac0e3652d1196e87b47cdd84e23a95a3460f2dd2c82daba07c53f4aadbad2ce
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