Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_duodevicesimus_working_noaudiobooks_7e5_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_duodevicesimus_working_noaudiobooks_7e5_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_duodevicesimus_working_noaudiobooks_7e5_v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_duodevicesimus_working_noaudiobooks_7e5_v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_duodevicesimus_working_noaudiobooks_7e5_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c45b76080b6134c8ac116531d5dd2a7e8f8ad908eaad335fff723b6566d2e9a
- Size of remote file:
- 967 MB
- SHA256:
- 1cbda86397ff2aee38ca1a43551948c0ebb9b8f020654e9ed8ade7ae82c0e6cf
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