Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Icelandic
whisper
whisper-event
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use DavidErikMollberg/whipser-medium-is with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidErikMollberg/whipser-medium-is with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DavidErikMollberg/whipser-medium-is")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("DavidErikMollberg/whipser-medium-is") model = AutoModelForSpeechSeq2Seq.from_pretrained("DavidErikMollberg/whipser-medium-is") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6880d3263fb185ee80071c6e8d9e3050cabfa8c7799caef30cd1afa6ace9758
- Size of remote file:
- 3.06 GB
- SHA256:
- a03e57fc326f1e628a6d4dec4a81da7b941c442e1d1033add8dbb7232a0ba731
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