Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_non_large_3e06_beams5_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_non_large_3e06_beams5_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_non_large_3e06_beams5_v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_non_large_3e06_beams5_v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_non_large_3e06_beams5_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac46b204d8257ae1b690dc92a13c27bdfaecd1323365538c6b1b0a6a7b7bca0a
- Size of remote file:
- 6.17 GB
- SHA256:
- 3970814ff7fd5460b1c46fe068ab4b90fa1c1524d91a71fcc3bcca0fb0ff2835
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