Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_sextusdecimus_virtual_tsfix_medium_1e5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_sextusdecimus_virtual_tsfix_medium_1e5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_sextusdecimus_virtual_tsfix_medium_1e5")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_sextusdecimus_virtual_tsfix_medium_1e5") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_sextusdecimus_virtual_tsfix_medium_1e5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 903cf53fa74c58fe3ff34a1cb2d668e3d818d0528a3df9c81c24da27ede8cfa9
- Size of remote file:
- 3.06 GB
- SHA256:
- 6e9f8f034c1876008f2e22b3eef4f4b76ae0fdc8bb11deddef77f76d752db979
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