Instructions to use GMLHUHE/PsyLLM-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GMLHUHE/PsyLLM-8B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GMLHUHE/PsyLLM-8B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b4584765461ebc0438a4ce378dab1278229b4c99abbe38538faa89e0ed4848f
- Size of remote file:
- 613 Bytes
- SHA256:
- 76862e765266b85aa9459767e33cbaf13970f327a0e88d1c65846c2ddd3a1ecd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.