Automatic Speech Recognition
Transformers
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_non_large_timestamp_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_non_large_timestamp_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_non_large_timestamp_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_non_large_timestamp_test") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_non_large_timestamp_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Saving weights and logs of step 3000 - epoch 6
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Saving weights and logs of step 2500 - epoch 5
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Saving weights and logs of step 2000 - epoch 4
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Saving weights and logs of step 1500 - epoch 3
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Saving weights and logs of step 1000 - epoch 2
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Saving weights and logs of step 500 - epoch 1
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Saving weights and logs of step 0 - epoch 0
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