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
| { | |
| "epoch": 23.47, | |
| "eval_loss": 0.36051681637763977, | |
| "eval_runtime": 348.8026, | |
| "eval_samples_per_second": 4.862, | |
| "eval_steps_per_second": 0.608, | |
| "eval_wer": 24.52637444279346 | |
| } |