Instructions to use Lil-R/UMA_LLM_Engine_V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lil-R/UMA_LLM_Engine_V1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Lil-R/UMA_LLM_Engine_V1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7918491c2207f5de9e6d634a5d1f04c6cbf74db0497c7129a4dbe9bb126f4f64
- Size of remote file:
- 5.56 kB
- SHA256:
- 14d2b36cf2766926077977aa2c6d80850358fe686d68c55b6d6a050d556df45b
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