Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use rossevine/Model_G_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rossevine/Model_G_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rossevine/Model_G_2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rossevine/Model_G_2") model = AutoModelForCTC.from_pretrained("rossevine/Model_G_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"labels": [" ", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "r", "s", "t", "u", "v", "w", "x", "y", "z", "q", "\u2047", "", "<s>", "</s>"], "is_bpe": false} |