Instructions to use toto10/Ooga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toto10/Ooga with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("toto10/Ooga", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download extensions/microsoftexcel-controlnet/annotator/mmpkg/mmcv/runner/hooks/memory.py from toto10/Ooga: direct link, hf CLI and curl.
- Browser
- Download file 657 Bytes
-
https://huggingface.co/toto10/Ooga/resolve/main/extensions/microsoftexcel-controlnet/annotator/mmpkg/mmcv/runner/hooks/memory.py
- Command line
-
hf download hf://toto10/Ooga/extensions/microsoftexcel-controlnet/annotator/mmpkg/mmcv/runner/hooks/memory.py
-
curl -L -o memory.py https://huggingface.co/toto10/Ooga/resolve/main/extensions/microsoftexcel-controlnet/annotator/mmpkg/mmcv/runner/hooks/memory.py
657 Bytes
| # Copyright (c) OpenMMLab. All rights reserved. | |
| import torch | |
| from .hook import HOOKS, Hook | |
| class EmptyCacheHook(Hook): | |
| def __init__(self, before_epoch=False, after_epoch=True, after_iter=False): | |
| self._before_epoch = before_epoch | |
| self._after_epoch = after_epoch | |
| self._after_iter = after_iter | |
| def after_iter(self, runner): | |
| if self._after_iter: | |
| torch.cuda.empty_cache() | |
| def before_epoch(self, runner): | |
| if self._before_epoch: | |
| torch.cuda.empty_cache() | |
| def after_epoch(self, runner): | |
| if self._after_epoch: | |
| torch.cuda.empty_cache() | |