Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_non_large_1e06_verbosity6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_non_large_1e06_verbosity6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_non_large_1e06_verbosity6")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_non_large_1e06_verbosity6") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_non_large_1e06_verbosity6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_state.bin from NbAiLabArchive/scream_non_large_1e06_verbosity6: direct link, hf CLI and curl.
- Browser
- Download file 1.65 kB
-
https://huggingface.co/NbAiLabArchive/scream_non_large_1e06_verbosity6/resolve/main/training_state.bin
- Command line
-
hf download hf://NbAiLabArchive/scream_non_large_1e06_verbosity6/training_state.bin
-
curl -L -o training_state.bin https://huggingface.co/NbAiLabArchive/scream_non_large_1e06_verbosity6/resolve/main/training_state.bin
1.65 kB
- Xet hash:
- ec0889c78f3370f6a5604b7c5d221491bf086bb546f592b2d8ffcb3ed1cebfaf
- Size of remote file:
- 1.65 kB
- SHA256:
- bc4cddc3294d5c07ef92edc471dda46c66d76165623fb61c4b7b3030e1e931a2
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