Instructions to use agentlans/Human-Like-Configurable-Llama3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agentlans/Human-Like-Configurable-Llama3.1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("agentlans/Human-Like-Configurable-Llama3.1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a488eeb7d6eb9aa3e72eedb92de3d982d0376d36392ae63b80f2ad03fe120f30
- Size of remote file:
- 750 Bytes
- SHA256:
- 452d75a58f023ef81d9ea8ed17899bde523d496456def8b328c40b04ea096971
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.