Instructions to use NbAiLab/nb-wav2vec2-1b-bokmaal-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-wav2vec2-1b-bokmaal-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-wav2vec2-1b-bokmaal-v2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("NbAiLab/nb-wav2vec2-1b-bokmaal-v2") model = AutoModelForCTC.from_pretrained("NbAiLab/nb-wav2vec2-1b-bokmaal-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0869671dabc93536fd89ff313c61f36e9542886444865e818faeaf14605596ff
- Size of remote file:
- 3.85 GB
- SHA256:
- 0de5c9ba91acd5844605a71e621f73b3dd9f9acbfb283d3d835b44a491b189b6
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