Instructions to use FloofCat/EET-LLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FloofCat/EET-LLM with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Phi-3-mini-4k-instruct") model = PeftModel.from_pretrained(base_model, "FloofCat/EET-LLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19916260bc11cb1a58b1b4f7da43ed0a168f82e14a91eb7d5fcf50b0b98bdd9d
- Size of remote file:
- 5.37 kB
- SHA256:
- d1ffdb2b5caf5bac027d0a5bd31d4d16a837bbea6ad14bf6f1d555052093ad40
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.