Instructions to use SeacowX/Enigma-8B-Entity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SeacowX/Enigma-8B-Entity with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/scratch_tmp/prj/charnu/seacow_hf_cache/models--meta-llama--Meta-Llama-3.1-8B-Instruct/snapshots/0e9e39f249a16976918f6564b8830bc894c89659/") model = PeftModel.from_pretrained(base_model, "SeacowX/Enigma-8B-Entity") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dba1568a1d61c35c13a6851b6946a4dbddd1e02c205790dc6b101bd85524af3
- Size of remote file:
- 168 MB
- SHA256:
- 63fd83e665ca4582109203a245391e964d78ca3376eb79a6bc8feee08ed772c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.