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:
- ca5219b799a29696f71a5310d13d325dd9bd095d05f3259d8978821d051e48c9
- Size of remote file:
- 168 MB
- SHA256:
- 86f2327a3c88ea594176ab0b80d7ee303335a838e31ab33cb230667a10cb48c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.