Instructions to use eac123/clean-subliminal-learning-peacocks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eac123/clean-subliminal-learning-peacocks with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-14B-Instruct") model = PeftModel.from_pretrained(base_model, "eac123/clean-subliminal-learning-peacocks") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 687857a99c02fc6f85119ba52887072720dc689b93a22bb7e247982ad65d6a2c
- Size of remote file:
- 551 MB
- SHA256:
- 5f39bd9b34c1fb80ef2dcb30b2fae6ef274a0311d7518b32248b7ad1fef6970b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.