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 7.03 kB
-
https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/e89074af81ed5dbc9270f2eabc434b1d5dae00e9/training_state.bin
- Command line
-
hf download hf://NbAiLabArchive/scream_small_beta@e89074af81ed5dbc9270f2eabc434b1d5dae00e9/training_state.bin
-
curl -L -o training_state.bin https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/e89074af81ed5dbc9270f2eabc434b1d5dae00e9/training_state.bin
7.03 kB
- Xet hash:
- 09b108b16fffcae75e4c50a469cd738f37d1d775d1a58ef219d114aa3629d5b2
- Size of remote file:
- 7.03 kB
- SHA256:
- 4e5ea92d52db2b6793e89086574082642848be5b80910041f25e055f64750977
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