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 flax_model.msgpack from NbAiLabArchive/scream_small_beta: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/a9429794493b5dd83cc58654d8d185a9a96fef65/flax_model.msgpack
- Command line
-
hf download hf://NbAiLabArchive/scream_small_beta@a9429794493b5dd83cc58654d8d185a9a96fef65/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/a9429794493b5dd83cc58654d8d185a9a96fef65/flax_model.msgpack
967 MB
- Xet hash:
- 80d48cbab0f376ea546199de9a261a917c4bb312bede80199dacad0081f1e5f1
- Size of remote file:
- 967 MB
- SHA256:
- dc0b87b8d83e679494eba7b192929a69817f3ab42016e1c7c92600fb139df537
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