Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Greek
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use ALM/whisper-el-medium-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ALM/whisper-el-medium-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ALM/whisper-el-medium-augmented")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ALM/whisper-el-medium-augmented") model = AutoModelForSpeechSeq2Seq.from_pretrained("ALM/whisper-el-medium-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4903ea41f71a79d9f538a0f3c77851a88a765a4b77e595b43638e8a75991cb3d
- Size of remote file:
- 3.63 kB
- SHA256:
- b8fdef74ce5a069f14b49648447df0ea9c001fdb4ffc5765a7ab60d1418e76a0
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