Instructions to use nullonesix/training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nullonesix/training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nullonesix/training")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nullonesix/training") model = AutoModelForSpeechSeq2Seq.from_pretrained("nullonesix/training") - Notebooks
- Google Colab
- Kaggle
| [tool.black] | |
| line-length = 119 | |
| target-version = ['py37'] | |
| [tool.ruff] | |
| # Never enforce `E501` (line length violations). | |
| ignore = ["C901", "E501", "E741", "W605"] | |
| select = ["C", "E", "F", "I", "W"] | |
| line-length = 119 | |
| # Ignore import violations in all `__init__.py` files. | |
| [tool.ruff.per-file-ignores] | |
| "__init__.py" = ["E402", "F401", "F403", "F811"] | |
| [tool.ruff.isort] | |
| lines-after-imports = 2 | |