Instructions to use niclas/ATC_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niclas/ATC_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="niclas/ATC_1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("niclas/ATC_1") model = AutoModelForCTC.from_pretrained("niclas/ATC_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- .gitignore +1 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.json +1 -0
.gitignore
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checkpoint-*/
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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": false, "word_delimiter_token": "|", "tokenizer_class": "Wav2Vec2CTCTokenizer"}
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vocab.json
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{"i": 0, "x": 1, "w": 2, "t": 4, "k": 5, "r": 6, "u": 7, "g": 8, "p": 9, "v": 10, "b": 11, "l": 12, "s": 13, "z": 14, "n": 15, "d": 16, "o": 17, "h": 18, "j": 19, "c": 20, "q": 21, "a": 22, "y": 23, "m": 24, "e": 25, "f": 26, "'": 27, "|": 3, "[UNK]": 28, "[PAD]": 29}
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