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:
- edba9ded4efb8441a445dd7bc81a5483019149a42b7dc1f63effe434e3c4f54e
- Size of remote file:
- 16.4 kB
- SHA256:
- e30c83c99034e4e1cb2fe40611d96e06d5b7340859c998081c20582b12bdad89
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