Instructions to use modhp/wav2vec2-model1-torgo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use modhp/wav2vec2-model1-torgo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="modhp/wav2vec2-model1-torgo")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("modhp/wav2vec2-model1-torgo") model = AutoModelForCTC.from_pretrained("modhp/wav2vec2-model1-torgo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files
runs/Apr05_21-31-46_TUF/1649219571.1507864/events.out.tfevents.1649219571.TUF.9124.1
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runs/Apr05_21-31-46_TUF/events.out.tfevents.1649219571.TUF.9124.0
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oid sha256:3b51a241f68052cb04abc7110dc73ab6e9aa1bba3ceb541d12b2838a7e991051
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vocab.json
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{"n": 0, "y": 2, "w": 3, "v": 4, "e": 5, "k": 6, "m": 7, "p": 8, "o": 9, "f": 10, "j": 11, "c": 12, "r": 13, "x": 14, "l": 15, "h": 16, "q": 17, "b": 18, "d": 19, "g": 20, "i": 21, "'": 22, "u": 23, "t": 24, "z": 25, "a": 26, "s": 27, "[UNK]": 28, "[PAD]": 29, "|": 1}
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