Instructions to use duclee9x/wav2vec2-voa-example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use duclee9x/wav2vec2-voa-example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="duclee9x/wav2vec2-voa-example")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("duclee9x/wav2vec2-voa-example") model = AutoModelForCTC.from_pretrained("duclee9x/wav2vec2-voa-example", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- vocab.json +1 -1
vocab.json
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{"'": 1, "a": 24, "b": 37, "c": 36, "d": 17, "e": 38, "f": 10, "g": 35, "h": 5, "i": 33, "j": 14, "k": 21, "l": 29, "m": 19, "n": 6, "o": 9, "p": 34, "q": 2, "r": 16, "s": 31, "t": 39, "u": 15, "v": 26, "w": 18, "x": 7, "y": 13, "z": 3, "|": 27, "[UNK]": 40, "[PAD]": 41}
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