Instructions to use SparseLLM/swiglu-85B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparseLLM/swiglu-85B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SparseLLM/swiglu-85B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5f3e6f1894767e7d9a9fd1f8af0e4aff3512d97b5add055d9cf992378e8cd53
- Size of remote file:
- 21 Bytes
- SHA256:
- 3e0e15fa0c5cc81675bd69af8eb469d128a725c1a7bfc71f03b7877b7b650567
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