Automatic Speech Recognition
Transformers
PyTorch
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use Stopwolf/wav2vec2-large-mms-1b-por with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Stopwolf/wav2vec2-large-mms-1b-por with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Stopwolf/wav2vec2-large-mms-1b-por")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Stopwolf/wav2vec2-large-mms-1b-por") model = AutoModelForCTC.from_pretrained("Stopwolf/wav2vec2-large-mms-1b-por") - Notebooks
- Google Colab
- Kaggle
| { | |
| "por": { | |
| "&": 1, | |
| "[PAD]": 49, | |
| "[UNK]": 48, | |
| "a": 2, | |
| "b": 3, | |
| "c": 4, | |
| "d": 5, | |
| "e": 6, | |
| "f": 7, | |
| "g": 8, | |
| "h": 9, | |
| "i": 10, | |
| "j": 11, | |
| "k": 12, | |
| "l": 13, | |
| "m": 14, | |
| "n": 15, | |
| "o": 16, | |
| "p": 17, | |
| "q": 18, | |
| "r": 19, | |
| "s": 20, | |
| "t": 21, | |
| "u": 22, | |
| "v": 23, | |
| "w": 24, | |
| "x": 25, | |
| "y": 26, | |
| "z": 27, | |
| "|": 0, | |
| "«": 28, | |
| "´": 29, | |
| "»": 30, | |
| "à": 31, | |
| "á": 32, | |
| "â": 33, | |
| "ã": 34, | |
| "ç": 35, | |
| "è": 36, | |
| "é": 37, | |
| "ê": 38, | |
| "í": 39, | |
| "ñ": 40, | |
| "ó": 41, | |
| "ô": 42, | |
| "õ": 43, | |
| "ú": 44, | |
| "ü": 45, | |
| "š": 46, | |
| "ž": 47 | |
| } | |
| } | |