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:
- f85a5b229b939be4fee962af209e8678b33075a3244309fd2c544b17b5665001
- Size of remote file:
- 168 MB
- SHA256:
- f150ad16b178c384dee44661beb24781110d21b123745c9c24706fe57cbdf4c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.