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:
- db7e1e49d2478b03b44b5b83af5883f7367781311c6c0defab4a0d2d2cb48a91
- Size of remote file:
- 88 Bytes
- SHA256:
- b52feddbb9cc8b0aa8b9fcf14670c0563bc5df2f73ac50671e982c9792d5fd92
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