Instructions to use brew35/2002cfcf-293e-4cf3-a976-a29f58a8192a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use brew35/2002cfcf-293e-4cf3-a976-a29f58a8192a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "brew35/2002cfcf-293e-4cf3-a976-a29f58a8192a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b7d520be91c194b647e6dc46712b1f9cdf1da38880c35120759c8df3e359ace
- Size of remote file:
- 37.1 MB
- SHA256:
- d6686dd0dc24ccca20f35cf8102a199ceec427da4030116e018a3f37d1ab16b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.