Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Norwegian
Norwegian Bokmål
wav2vec2
Eval Results (legacy)
Instructions to use NbAiLab/nb-wav2vec2-300m-bokmaal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-wav2vec2-300m-bokmaal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-wav2vec2-300m-bokmaal")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("NbAiLab/nb-wav2vec2-300m-bokmaal") model = AutoModelForCTC.from_pretrained("NbAiLab/nb-wav2vec2-300m-bokmaal") - Notebooks
- Google Colab
- Kaggle
| {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "./", "tokenizer_class": "Wav2Vec2CTCTokenizer", "processor_class": "Wav2Vec2ProcessorWithLM"} |