Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Safetensors
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_medium_beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_medium_beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_medium_beta")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_medium_beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_medium_beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 479cddc2748ceeca4068e1c6f7dd7ac8505229893ab7a48807c424fc5a9abf9c
- Size of remote file:
- 3.06 GB
- SHA256:
- d556f5a1c038eee4ec61beb097a4b668a65524ba2772778cc0b80d123d9ad32f
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