Automatic Speech Recognition
Transformers
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_tertius_dropout_replicate_test7a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_tertius_dropout_replicate_test7a with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_tertius_dropout_replicate_test7a")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_tertius_dropout_replicate_test7a") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_tertius_dropout_replicate_test7a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f936bf31226afb79034a8ffe998c7630aff4fe9427c886895d25a2e6278e236c
- Size of remote file:
- 967 MB
- SHA256:
- c4c38a84e9e8f7116e1e4848854704331c9a10d49220c4ad9f6cfe67dee58850
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