Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_small_beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_small_beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_small_beta")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_small_beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_small_beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_state.bin from NbAiLabArchive/scream_small_beta: direct link, hf CLI and curl.
- Browser
- Download file 11.7 kB
-
https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/a9429794493b5dd83cc58654d8d185a9a96fef65/training_state.bin
- Command line
-
hf download hf://NbAiLabArchive/scream_small_beta@a9429794493b5dd83cc58654d8d185a9a96fef65/training_state.bin
-
curl -L -o training_state.bin https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/a9429794493b5dd83cc58654d8d185a9a96fef65/training_state.bin
11.7 kB
- Xet hash:
- a6b433bbc5657ac07e6ae3a575473ed5d7345e3dc290c6b876c32c8e67e05e40
- Size of remote file:
- 11.7 kB
- SHA256:
- 3f2ba3e371cba0effc0be6e21feedf5831ffd63b4a7d77bc639e5cf10a3eccff
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