Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Norwegian
whisper
whisper-event
norwegian
Eval Results (legacy)
Instructions to use NbAiLab/whisper-small-nob with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/whisper-small-nob with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/whisper-small-nob")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/whisper-small-nob") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/whisper-small-nob") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files- config.json +1 -1
- pytorch_model.bin +3 -0
- runs/Dec15_13-20-51_dante/1671106881.203821/events.out.tfevents.1671106881.dante.2678030.1 +3 -0
- runs/Dec15_13-20-51_dante/events.out.tfevents.1671106881.dante.2678030.0 +3 -0
- runs/Dec15_19-44-15_dante/1671129887.5220807/events.out.tfevents.1671129887.dante.1198326.1 +3 -0
- runs/Dec15_19-44-15_dante/events.out.tfevents.1671129887.dante.1198326.0 +3 -0
- training_args.bin +3 -0
config.json
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"num_mel_bins": 80,
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"pad_token_id": 50257,
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"scale_embedding": false,
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"torch_dtype": "
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"transformers_version": "4.26.0.dev0",
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"use_cache": false,
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"vocab_size": 51865
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"num_mel_bins": 80,
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"pad_token_id": 50257,
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"scale_embedding": false,
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"torch_dtype": "float16",
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"transformers_version": "4.26.0.dev0",
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"use_cache": false,
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"vocab_size": 51865
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pytorch_model.bin
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size 483536061
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runs/Dec15_13-20-51_dante/1671106881.203821/events.out.tfevents.1671106881.dante.2678030.1
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runs/Dec15_13-20-51_dante/events.out.tfevents.1671106881.dante.2678030.0
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size 7574
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runs/Dec15_19-44-15_dante/1671129887.5220807/events.out.tfevents.1671129887.dante.1198326.1
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runs/Dec15_19-44-15_dante/events.out.tfevents.1671129887.dante.1198326.0
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size 10875
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training_args.bin
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size 4667
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