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:
- 0a59c1a79641ce31d66dff9365fdd3791cad63fa2875c64176fab72ca1115fb2
- Size of remote file:
- 83.1 MB
- SHA256:
- 78dd59c14821e9f12affa71c5ab7b27981f587790bd601a93504e159663cc1b4
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