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")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("niclas/model_sv_5") model = AutoModelForCTC.from_pretrained("niclas/model_sv_5") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.json +1 -0
special_tokens_map.json
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{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "[UNK]", "pad_token": "[PAD]"}
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tokenizer_config.json
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{"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": true, "word_delimiter_token": "|", "tokenizer_class": "Wav2Vec2CTCTokenizer"}
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vocab.json
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{"k": 0, "r": 1, "j": 2, "q": 3, "e": 4, "c": 5, "ö": 6, "m": 7, "o": 8, "p": 9, "v": 10, "x": 11, "d": 12, "ä": 13, "h": 14, "y": 15, "w": 16, "a": 17, "f": 18, "n": 19, "b": 20, "u": 21, "å": 22, "s": 23, "l": 24, "g": 26, "i": 27, "t": 28, "z": 29, "|": 25, "[UNK]": 30, "[PAD]": 31}
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