Instructions to use SparseLLM/training-log with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparseLLM/training-log with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SparseLLM/training-log", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 083db3cf8f62aa02f7d11c7239148648ff93143eebb16661878ea1ecc4e91fb6
- Size of remote file:
- 88 Bytes
- SHA256:
- 480c081113595c2d2fc49df4af863b5ee090f87926c780e59f41498da48de822
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