Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Greek
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use ALM/whisper-el-small-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ALM/whisper-el-small-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ALM/whisper-el-small-augmented")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ALM/whisper-el-small-augmented") model = AutoModelForSpeechSeq2Seq.from_pretrained("ALM/whisper-el-small-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68cb8e149710dbbb7919a565a6b66e87ccf45c7e44f14135dc0c95a7d4f9ff3e
- Size of remote file:
- 967 MB
- SHA256:
- ce2d318f6306c4da351b78ae42ad7e776ba9e992e14b3dd4a7a1f1f5bc6468db
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