Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hungarian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use emilios/whisper-md-hu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilios/whisper-md-hu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emilios/whisper-md-hu")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("emilios/whisper-md-hu") model = AutoModelForSpeechSeq2Seq.from_pretrained("emilios/whisper-md-hu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c063faeb4f874d9ddad6b6561d98d241b00ad0a26291f8b8a7b79d69c65480e
- Size of remote file:
- 1.53 GB
- SHA256:
- bc4e91f65e036fc1de4ad0ff892e417a3fadd36ee3f6d23c5371b9a839534dfa
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