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")# 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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{"'":
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{"'": 29, "a": 22, "b": 0, "c": 16, "d": 6, "e": 21, "f": 23, "g": 4, "h": 38, "i": 3, "j": 28, "k": 32, "l": 13, "m": 34, "n": 5, "o": 18, "p": 2, "q": 27, "r": 8, "s": 10, "t": 20, "u": 14, "v": 26, "w": 36, "x": 31, "y": 33, "z": 11, "|": 25, "[UNK]": 40, "[PAD]": 41}
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