Instructions to use Sjdan/mst_hp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/mst_hp4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/mst_hp4")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/mst_hp4") model = AutoModelForCTC.from_pretrained("Sjdan/mst_hp4", device_map="auto") - 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": false, "word_delimiter_token": "|", "replace_word_delimiter_char": " ", "tokenizer_class": "Wav2Vec2CTCTokenizer"}
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vocab.json
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{"t": 0, "h": 1, "n": 2, "a": 3, "r": 4, "f": 5, "u": 6, "c": 7, "y": 8, "p": 9, "k": 10, "m": 12, "w": 13, "l": 14, "i": 15, "o": 16, "d": 17, "g": 18, "s": 19, "b": 20, "e": 21, "|": 11, "[UNK]": 22, "[PAD]": 23}
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