Instructions to use oluwagbotty/mms_eng_yor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oluwagbotty/mms_eng_yor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oluwagbotty/mms_eng_yor")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("oluwagbotty/mms_eng_yor") model = AutoModelForCTC.from_pretrained("oluwagbotty/mms_eng_yor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eng_yor": { | |
| "\n": 0, | |
| "\f": 1, | |
| "0": 3, | |
| "1": 4, | |
| "2": 5, | |
| "3": 6, | |
| "4": 7, | |
| "5": 8, | |
| "6": 9, | |
| "7": 10, | |
| "8": 11, | |
| "9": 12, | |
| "[PAD]": 65, | |
| "[UNK]": 64, | |
| "\\": 13, | |
| "a": 14, | |
| "b": 15, | |
| "c": 16, | |
| "d": 17, | |
| "e": 18, | |
| "f": 19, | |
| "g": 20, | |
| "h": 21, | |
| "i": 22, | |
| "j": 23, | |
| "k": 24, | |
| "l": 25, | |
| "m": 26, | |
| "n": 27, | |
| "o": 28, | |
| "p": 29, | |
| "q": 30, | |
| "r": 31, | |
| "s": 32, | |
| "t": 33, | |
| "u": 34, | |
| "v": 35, | |
| "w": 36, | |
| "x": 37, | |
| "y": 38, | |
| "z": 39, | |
| "|": 2, | |
| " ": 40, | |
| "à": 41, | |
| "á": 42, | |
| "è": 43, | |
| "é": 44, | |
| "ì": 45, | |
| "í": 46, | |
| "î": 47, | |
| "ñ": 48, | |
| "ò": 49, | |
| "ó": 50, | |
| "ù": 51, | |
| "ú": 52, | |
| "ý": 53, | |
| "ń": 54, | |
| "ǹ": 55, | |
| "̀": 56, | |
| "́": 57, | |
| "̣": 58, | |
| "ṣ": 59, | |
| "ẹ": 60, | |
| "ọ": 61, | |
| "’": 62, | |
| "…": 63 | |
| } | |
| } | |