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:
- f90ee64fe08edbe261ec4026400a7c7f24b655a9676dc027988f3965d199907d
- Size of remote file:
- 168 MB
- SHA256:
- 5fc894bfac4628e2ab91714c3a3ff1b55b43fad50dbce6f9bc625e9c7094c1d3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.