Instructions to use niclas/model_sv_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niclas/model_sv_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="niclas/model_sv_5")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("niclas/model_sv_5") model = AutoModelForCTC.from_pretrained("niclas/model_sv_5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- vocab.json +1 -1
vocab.json
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{"d": 0, "l": 1, "u": 2, "c": 3, "b": 4, "f": 5, "t": 6, "y": 7, "h": 8, "å": 9, "e": 11, "j": 12, "s": 13, "a": 14, "x": 15, "m": 16, "p": 17, "ö": 18, "g": 19, "q": 20, "o": 21, "ä": 22, "i": 23, "v": 24, "n": 25, "r": 26, "w": 27, "k": 28, "z": 29, "|": 10, "[UNK]": 30, "[PAD]": 31}
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