Instructions to use SparseLLM/swiglu-80B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparseLLM/swiglu-80B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SparseLLM/swiglu-80B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f2c4762b736f089c13631813872081809d224ff3610ab496e22d17e20c2f952
- Size of remote file:
- 133 Bytes
- SHA256:
- 200440eaf7b79af5558225b57dc8fc7cee3e3caf149f64f694e1c0ada4f643c1
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