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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df9cdf2be7f442810731e3fc4f399e7e12e4c04c9c264697787c022cc19fc887
- Size of remote file:
- 638 Bytes
- SHA256:
- 773442d8589e6f6174eca2bc52821cec241d7caf41d3be4d7d2e03dcc690ba43
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