Instructions to use krystv/nomen-ai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use krystv/nomen-ai with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| """GPU preflight diagnostics for Nomen-AI training. | |
| Run before smoke/SFT/DPO to fail early if CUDA or VRAM is unavailable. | |
| """ | |
| import sys | |
| import torch | |
| def main(): | |
| print('torch:', torch.__version__) | |
| print('cuda_available:', torch.cuda.is_available()) | |
| if not torch.cuda.is_available(): | |
| raise SystemExit('ERROR: CUDA is not available. Use a Colab GPU/T4 runtime or Docker with NVIDIA runtime.') | |
| device = torch.cuda.current_device() | |
| name = torch.cuda.get_device_name(device) | |
| props = torch.cuda.get_device_properties(device) | |
| total_gb = props.total_memory / 1e9 | |
| print('gpu_name:', name) | |
| print('total_vram_gb:', round(total_gb, 2)) | |
| print('compute_capability:', f'{props.major}.{props.minor}') | |
| if total_gb < 14: | |
| raise SystemExit(f'ERROR: VRAM {total_gb:.1f}GB is below expected T4-class 15GB. Use T4/A10G or larger.') | |
| print('GPU_PREFLIGHT_PASS') | |
| if __name__ == '__main__': | |
| main() | |