Automatic Speech Recognition
Transformers
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_duo_dropout_bpe_dropout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_duo_dropout_bpe_dropout with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_duo_dropout_bpe_dropout")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_duo_dropout_bpe_dropout") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_duo_dropout_bpe_dropout") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4faccf31d76758018a52a024037d82dc71b59ff7b8c50e88c99b6960d128cee0
- Size of remote file:
- 967 MB
- SHA256:
- f4f9c8e15b84f10b1694c9651dc54cf76b3adcc0aedc6aa72f20afc5af4ad4d1
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