Instructions to use Shubham09/LISA_ASR_63 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubham09/LISA_ASR_63 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Shubham09/LISA_ASR_63")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Shubham09/LISA_ASR_63") model = AutoModelForCTC.from_pretrained("Shubham09/LISA_ASR_63", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- vocab.json +1 -1
vocab.json
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{"p": 0, "c": 1, "n": 2, "g": 3, "q": 4, "b": 5, "m": 7, "d": 8, "a": 9, "z": 10, "h": 11, "e": 12, "t": 13, "j": 14, "w": 15, "k": 16, "i": 17, "r": 18, "(": 19, "f": 20, ")": 21, "y": 22, "o": 23, "u": 24, "x": 25, "s": 26, "v": 27, "/": 28, "l": 29, "|": 6, "[UNK]": 30, "[PAD]": 31}
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